repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
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values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/adjective_freq.py | features/audio_features/helpers/pyAudioLex/adjective_freq.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: adjective_freq
Frequency of a POS tag is computed by dividing the total number of words
with that tag by the total number of words spoken by the subject in the
recording.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
def adj... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/wpm.py | features/audio_features/helpers/pyAudioLex/wpm.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: wpm
Used to calculate words per minute.
'''
def wpm(s, tokens, duration):
r = float(duration / 60)
return len(tokens) / r | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/question_ratio.py | features/audio_features/helpers/pyAudioLex/question_ratio.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: question_ratio
Patients are more likely to forget details in the middle of conversation,
to not understand the questions, or to forget the context of the question.
In those cases, they tend to ask the interviewer to repeat the question or
they get confused, tal... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/conjunction_freq.py | features/audio_features/helpers/pyAudioLex/conjunction_freq.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: conjunction_freq
Frequency of a POS tag is computed by dividing the total number of words
with that tag by the total number of words spoken by the subject in the
recording.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
def c... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/standardized_word_entropy.py | features/audio_features/helpers/pyAudioLex/standardized_word_entropy.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: standardized_word_entropy
One of the earliest parts of the brain to be damaged by Alzheimer's
disease is the part of the brain that deals with language ability [5].
We hypothesize that this may cause a degradation in the variety of words
and word combinations t... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/filler_ratio.py | features/audio_features/helpers/pyAudioLex/filler_ratio.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: filler_ratio
Filler sounds such as 'ahm' and 'ehm' are used by people in spoken language
when they think about what to say next. We hypothesize that they may be used
more frequently by the patients because of slow thinking and memory recall
processes. Patients ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/audio_.py | features/audio_features/helpers/pyAudioLex/audio_.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: audio
Used to process all audio features based heavily on pyAudioAnalysis
'''
from pyAudioAnalysis import audioBasicIO
from pyAudioAnalysis import audioFeatureExtraction
import wave
import contextlib
# get duration
def get_duration(filepath):
try:
wavefile... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/pronoun_freq.py | features/audio_features/helpers/pyAudioLex/pronoun_freq.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: pronoun_freq
Frequency of a POS tag is computed by dividing the total number of words
with that tag by the total number of words spoken by the subject in the
recording.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
def prono... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/brunets_index.py | features/audio_features/helpers/pyAudioLex/brunets_index.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: brunets_index
Brunet's index (W) quantifies lexical richness [20]. It is
calculated as W = N^V^-0.165, where N is the total text length and V is the
total vocabulary. Lower values of W correspond to richer texts. As with
standardized word entropy, stemming is d... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/adverb_freq.py | features/audio_features/helpers/pyAudioLex/adverb_freq.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: adverb_freq
Frequency of a POS tag is computed by dividing the total number of words
with that tag by the total number of words spoken by the subject in the
recording.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
def adverb... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/pronoun_to_noun_ratio.py | features/audio_features/helpers/pyAudioLex/pronoun_to_noun_ratio.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: pronoun_to_noun_ratio
Pronoun-to-noun ratio is the ratio of the total number of pronouns to
the total number of nouns.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
def pronoun_to_noun_ratio(s, tokens = None):
if tokens == ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/type_token_ratio.py | features/audio_features/helpers/pyAudioLex/type_token_ratio.py | '''
@package: pyAudioLex
@author: Drew Morris
@module: type_token_ratio
A pattern that we noticed in the recordings of the Alzheimer's
patients is the frequency of repetitions in conversation. Patients tend
to forget what they have said and to repeat it elsewhere in the
conversation. The metric that we used to meas... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/tests/run_tests.py | features/audio_features/helpers/pyAudioLex/tests/run_tests.py | import sys
sys.path.append('..')
import wave
import contextlib
import glob
import json
import pyAudioLex
from colorama import Fore, Back, Style
default_format = '.3f'
# question_ratio
question_ratio = pyAudioLex.question_ratio('What time is it? What day is it?')
print('question_ratio', format(question_ratio, default_... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/grammar/get_grammar.py | features/audio_features/helpers/pyAudioLex/text_features/grammar/get_grammar.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: get_grammar
This script takes in a text sample and outputs 85140 grammar features.
Specifically, it extracts grammar from permutations of various parts of
speech in series.
For example, for the sentence 'I ate ham' it would be saved as
[Pronoun, Verb, Noun] fo... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/in_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/in_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: in_freq
in = preposition or conjunction, suborbinating
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def in_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nns_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nns_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: nns_freq
#nns = noun, common, plural
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def nns_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(tok... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/ls_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/ls_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: ls_freq
#ls = list item marker
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def ls_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jj_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jj_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: jj_freq
#jj = adjective or numeral, ordinal
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def jj_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Count... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbp_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbp_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vbp_freq
#vbp = verb, present tense, not 3rd person singular
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vbp_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/wdt_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/wdt_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: wdt_freq
#wdt = WH-determiner
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def wdt_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/dt_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/dt_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: dt_freq
#dt = determiner frequency
increased use of determiners a signal for schizophrenia.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def dt_freq(importtext):
text=word_tokenize(impo... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/wp_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/wp_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: wrb_freq
#wrb = wh-adverb
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def wrb_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for word... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rbs_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rbs_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: rp_freq
rp = particle
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def rp_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for word, tok... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/ex_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/ex_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: ex_freq
#ex = existential there
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def ex_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token fo... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vb_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vb_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vb_freq
#vb = verb, base form
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vb_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for w... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rbr_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rbr_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: rbr_freq
#rbr = adverb, comparative
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def rbr_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(toke... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jjs_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jjs_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: jjs_freq
#jjs = adjective, superlative
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def jjs_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(t... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/to_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/to_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: to_freq
#to = 'to' as a preposition or infinitive marker
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def to_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/uh_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/uh_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: uh_freq
#uh = interjection frequency
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def uh_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(toke... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/genitive_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/genitive_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: genetive_freq
#pos = genitive marker ('s)
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def genitive_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=C... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbg_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbg_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vbg_freq
#vbg = verb, prsent participle or gerund
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vbg_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/cc_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/cc_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: cc_freq
In grammar, a conjunction (abbreviated conj or cnj) is a part of speech
that connects words, phrases, or clauses that are called the conjuncts
of the conjoining construction. The term discourse marker is mostly used
for conjunctions joining sentences. Th... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jjr_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/jjr_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: jjr_freq
#jjr = adjective, comparative
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def jjr_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(t... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbd_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbd_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vbd_freq
#vbd = verb, past tense
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vbd_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token f... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbz_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbz_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vbz_freq
#vbz = verb, present tense, 3rd person singular
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vbz_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(tex... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nn_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nn_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: nn_freq
#nn = noun, common, singular or mass
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def nn_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Coun... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbn_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/vbn_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: vbn_freq
#vbn = verb, past participle
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def vbn_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(to... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/cd_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/cd_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: cd_freq
#cd = numeral, cardinal - also a number frequency.
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def cd_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(te... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nnp_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/nnp_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: nnp_freq
#nnp = noun, proper, singular
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def nnp_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/prp2_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/prp2_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: prp2_freq
prp$ - pronoun, possessive
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def prp2_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(to... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/pdt_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/pdt_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: pdt_freq
#pdt = pre-determiner
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def pdt_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rb_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/rb_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: rb_freq
#rb = adverb
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def rb_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token for word, toke... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/parts of speech/prp_freq.py | features/audio_features/helpers/pyAudioLex/text_features/parts of speech/prp_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: prp_freq
#prp = pronoun, personal
'''
from nltk.tokenize import word_tokenize
from nltk.tag import pos_tag, map_tag
from collections import Counter
def prp_freq(importtext):
text=word_tokenize(importtext)
tokens=nltk.pos_tag(text)
c=Counter(token ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/freq_dist.py | features/audio_features/helpers/pyAudioLex/text_features/words/freq_dist.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: freq_dist
outputs most frequent to least frequent words
'''
from nltk.tokenize import word_tokenize
from nltk import FreqDist
def freq_dist(importtext):
text=word_tokenize(importtext)
fdist1=FreqDist(text)
distribution=fdist1.most_common(len(... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/polarity.py | features/audio_features/helpers/pyAudioLex/text_features/words/polarity.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: polarity
Take in a text sample and output the average, standard deviation, and variance
polarity. (+) indicates happy and (-) indicates sad, 0 is neutral.
'''
import nltk
from nltk import word_tokenize
from textblob import TextBlob
import numpy as np
def pol... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/datewords_freq.py | features/audio_features/helpers/pyAudioLex/text_features/words/datewords_freq.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: datwords_freq
Take in a text sample and output frequency of date-related words.
'''
import nltk
from nltk import word_tokenize
def datewords_freq(importtext):
text=word_tokenize(importtext)
datewords=['time','monday','tuesday','wednesday','thursday','... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/word_endings.py | features/audio_features/helpers/pyAudioLex/text_features/words/word_endings.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: word_endings
Given a word ending (e.g. '-ed'), output the words with that ending and the associated count.
'''
from nltk import word_tokenize
import re
def word_endings(importtext,ending):
text=word_tokenize(importtext)
#number of words endi... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/emotion_freqs.py | features/audio_features/helpers/pyAudioLex/text_features/words/emotion_freqs.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: emotion_freqs
Take in a text sample and output a range of emotional frequencies.
The script does this for looking for specific hotwords related to the 7 main emotions:
fear, anger, sadness, joy, disgust, surprise, trust, and anticipation.
Note we will train th... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/word_repeats.py | features/audio_features/helpers/pyAudioLex/text_features/words/word_repeats.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: word_repeats
Word repeats on average every 10 words (important for psychosis).
Typical repeated word output:
the
the
the
the
to
to
to
to
on
on
,
,
If words are typically not articles like 'the', it could indicate a thought disorder.
'''
from nltk import wor... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/num_sentences.py | features/audio_features/helpers/pyAudioLex/text_features/words/num_sentences.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: num_sentences
Total number of sentences, as calculated by punctuation marks:
Periods (.),
Interjections (!),
Questions (?).
'''
def num_sentences(importtext):
#actual number of periods
periods=importtext.count('.')
#count number of questions
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/subjectivity.py | features/audio_features/helpers/pyAudioLex/text_features/words/subjectivity.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: subjectivity
Take in a text sample and output the average, standard deviation, and variance
subjectivity.
'''
import nltk
from nltk import word_tokenize
from textblob import TextBlob
import numpy as np
def subjectivity(importtext):
text=word_tokenize(im... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/text_features/words/word_stats.py | features/audio_features/helpers/pyAudioLex/text_features/words/word_stats.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: word_stats
Take in a text sample and output the average word length,
the maximum word length, the minimum word length,
the variance of the vocabulary, and the standard deviation of the vocabulary.
All of this is done by counting the length of individual words f... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/audioFeatures/audio_features.py | features/audio_features/helpers/pyAudioLex/audioFeatures/audio_features.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: audio_features
#These are all audio features extracted with librosa library.
See the documentation here: https://librosa.github.io/librosa/
All these features are represented as the mean, standard deviation, variance,
median, min, and max.
Note that another ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/audioFeatures/audio_time_features.py | features/audio_features/helpers/pyAudioLex/audioFeatures/audio_time_features.py | '''
@package: pyAudioLex
@author: Jim Schwoebel
@module: audio_time_features
#Note that another library exists for time-series features
(e.g. at 100 ms timescale). Uses audio_features library.
See the documentation here: https://librosa.github.io/librosa/
All these features are represented as the mean, standard dev... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/audioFeatures/__init__.py | features/audio_features/helpers/pyAudioLex/audioFeatures/__init__.py | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false | |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pyAudioLex/audioFeatures/standard_feature_array.py | features/audio_features/helpers/pyAudioLex/audioFeatures/standard_feature_array.py | import os
import librosa
import numpy as np
from pydub import AudioSegment
def featurize(wavfile):
#initialize features
hop_length = 512
n_fft=2048
#load file
y, sr = librosa.load(wavfile)
#extract mfcc coefficients
mfcc = librosa.feature.mfcc(y=y, sr=sr, hop_length=hop_length, n_mfcc=13)
mfcc_delta... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/pysptk/pysptk_features.py | features/audio_features/helpers/pysptk/pysptk_features.py | import seaborn, pysptk, matplotlib
import numpy as np
from scipy.io import wavfile
# get statistical features in numpy
def stats(matrix):
mean=np.mean(matrix)
std=np.std(matrix)
maxv=np.amax(matrix)
minv=np.amin(matrix)
median=np.median(matrix)
output=np.array([mean,std,maxv,minv,median])
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/sa/features/signal.py | features/audio_features/helpers/sa/features/signal.py | import numpy as np
import peakutils as pu
def get_F_0( signal, rate, time_step = 0.0, min_pitch = 75, max_pitch = 600,
max_num_cands = 15, silence_thres = .03, voicing_thres = .45,
octave_cost = .01, octave_jump_cost = .35,
voiced_unvoiced_cost = .14, accurate = False, pulse = Fal... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | true |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/myprosody/setup.py | features/audio_features/helpers/myprosody/setup.py | from setuptools import setup
long_description="""*** Version-10 release: two new functions were added ***
The two new functions deploy different Machine Learning algorithms to estimate the speakers' spoken
language proficiency levels (only the prosody aspect not semantically).
Prosody is the study of the tune an... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/myprosody/myprosody.py | features/audio_features/helpers/myprosody/myprosody.py | import parselmouth
from parselmouth.praat import call, run_file
import glob
import pandas as pd
import numpy as np
import scipy
from scipy.stats import binom
from scipy.stats import ks_2samp
from scipy.stats import ttest_ind
import os
def myspsyl(m,p):
sound=p+"/"+"dataset"+"/"+"audioFiles"+"/"+m+".wav"
source... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/setup.py | features/audio_features/helpers/surfboard/setup.py | from setuptools import setup
setup(
name="surfboard",
version="0.2.0",
description="Novoic's audio feature extraction library https://novoic.com",
url="http://github.com/novoic/surfboard",
author="Raphael Lenain",
author_email="raphael@novoic.com",
license="GPL-3.0",
packages=["surfboar... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/docs/conf.py | features/audio_features/helpers/surfboard/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/feature_extraction_multiprocessing.py | features/audio_features/helpers/surfboard/surfboard/feature_extraction_multiprocessing.py | #!/usr/bin/env python
"""This file contains functions to compute features with multiprocessing."""
from multiprocessing import Pool
from functools import partial
import pandas as pd
from tqdm import tqdm
from .feature_extraction import (
extract_features_from_waveform,
)
from .sound import Waveform
def load_... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/sound.py | features/audio_features/helpers/surfboard/surfboard/sound.py | #!/usr/bin/env python
"""This file contains the central Waveform class of the surfboard package, and all the corresponding methods"""
import librosa
from scipy.signal import cwt, morlet
import numpy as np
from . import (
jitters,
shimmers,
formants,
spectrum,
hnr,
dfa,
)
from .misc_components... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | true |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/statistics.py | features/audio_features/helpers/surfboard/surfboard/statistics.py | """This file contains the class which computes statistics from numpy arrays to turn components into features."""
from scipy.stats import (
kurtosis,
skew,
)
import numpy as np
class Barrel:
"""This class is used to instantiate components computed in the surfboard package.
It helps us compute statist... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/utils.py | features/audio_features/helpers/surfboard/surfboard/utils.py | #!/usr/bin/env python
"""This file contains a variety of helper functions for the surfboard package."""
import os
import numpy as np
from scipy.signal import (
deconvolve,
)
def metric_slidingwindow(frame_length, hop_length, truncate_end=False):
"""We use this decorator to decorate functions which take a s... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/feature_extraction.py | features/audio_features/helpers/surfboard/surfboard/feature_extraction.py | #!/usr/bin/env python
"""This file contains functions to compute features."""
import numpy as np
import pandas as pd
from tqdm import tqdm
from .sound import Waveform
from .statistics import Barrel
def load_waveforms_from_paths(paths, sample_rate):
"""Loads waveforms from paths using multiprocessing"""
pro... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/dfa.py | features/audio_features/helpers/surfboard/surfboard/dfa.py | import numpy as np
def get_deviation_for_dfa(signal, window_length):
"""Given a signal, compute the trend value for one window length, as per
https://link.springer.com/article/10.1186/1475-925X-6-23
In order to get the overall DFA (detrended fluctuation analysis),
compute this for a variety of window ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/__init__.py | features/audio_features/helpers/surfboard/surfboard/__init__.py | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false | |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/formants.py | features/audio_features/helpers/surfboard/surfboard/formants.py | """This code is inspired by the following repository:
https://github.com/manishmalik/Voice-Classification/blob/master/rootavish/formant.py
More importantly, by the following Matlab code:
https://uk.mathworks.com/help/signal/ug/formant-estimation-with-lpc-coefficients.html
The implementation is ours. These values have b... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/spectrum.py | features/audio_features/helpers/surfboard/surfboard/spectrum.py | """Spectrum features. The code in this file is inspired by audiocontentanalysis.org
For more details, visit the pyACA package: https://github.com/alexanderlerch/pyACA
"""
import numpy as np
def summed_magnitude_spectrum(magnitude_spectrum, keepdims=True):
summed_magnitude_spectrum = magnitude_spectrum.sum(0, kee... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/misc_components.py | features/audio_features/helpers/surfboard/surfboard/misc_components.py | #!/usr/bin/env python
"""This file contains components which do not fall under one category."""
import librosa
import pyloudnorm as pyln
import numpy as np
from scipy.stats import kurtosis
from scipy.signal import lfilter
from pysptk import swipe, rapt
from .utils import (
metric_slidingwindow,
numseconds_t... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/hnr.py | features/audio_features/helpers/surfboard/surfboard/hnr.py | """This function is inspired by the Speech Analysis repository at
https://github.com/brookemosby/Speech_Analysis
"""
import numpy as np
import peakutils as pu
def get_harmonics_to_noise_ratio(
waveform, sample_rate, min_pitch=75.0, silence_threshold=0.1, periods_per_window=4.5
):
"""Given a waveform, its sam... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/jitters.py | features/audio_features/helpers/surfboard/surfboard/jitters.py | #!/usr/bin/env python
"""This file contains all the functions needed to compute the jitters of a waveform."""
import numpy as np
from .utils import (
shifted_sequence,
)
def validate_frequencies(frequencies, p_floor, p_ceil, max_p_factor):
"""Given a sequence of frequencies, [f1, f2, ..., fn], a minimum pe... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/shimmers.py | features/audio_features/helpers/surfboard/surfboard/shimmers.py | #!/usr/bin/env python
"""This file contains all the functions needed to compute the shimmers of a waveform."""
import numpy as np
from .jitters import validate_frequencies
from .utils import (
shifted_sequence,
peak_amplitude_slidingwindow,
)
def validate_amplitudes(amplitudes, frequencies, max_a_factor, p... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/tests/__init__.py | features/audio_features/helpers/surfboard/surfboard/tests/__init__.py | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false | |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/tests/test_feature_extraction.py | features/audio_features/helpers/surfboard/surfboard/tests/test_feature_extraction.py | import os
import pytest
import yaml
import pandas as pd
import numpy as np
from surfboard import sound
from surfboard.utils import example_audio_file
from surfboard.feature_extraction import (
extract_features,
extract_features_from_paths
)
@pytest.fixture
def flat_waveform():
wave = np.ones((24000,))
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/tests/test_barrel.py | features/audio_features/helpers/surfboard/surfboard/tests/test_barrel.py | import pytest
import numpy as np
from surfboard import statistics
@pytest.fixture
def barrel():
feature = np.ones((25, 267))
return statistics.Barrel(feature)
def test_barrel_constructor(barrel):
feat = barrel()
assert (feat == np.ones((25, 267))).all()
def test_first_derivative(barrel):
d1 ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/audio_features/helpers/surfboard/surfboard/tests/test_sound.py | features/audio_features/helpers/surfboard/surfboard/tests/test_sound.py | import pytest
import numpy as np
from surfboard import sound
from surfboard.utils import example_audio_file
@pytest.fixture
def flat_waveform():
wave = np.ones((24000,))
return sound.Waveform(signal=wave, sample_rate=24000)
@pytest.fixture
def waveform():
filename = example_audio_file('a')
return ... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/video_features/y8m_features.py | features/video_features/y8m_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/video_features/video_features.py | features/video_features/video_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/video_features/featurize.py | features/video_features/featurize.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/video_features/helpers/tesseract_features.py | features/video_features/helpers/tesseract_features.py | import os, sys, time
from PIL import Image
import pytesseract
def prev_dir(directory):
g=directory.split('/')
# print(g)
lastdir=g[len(g)-1]
i1=directory.find(lastdir)
directory=directory[0:i1]
return directory
directory=os.getcwd()
prevdir=prev_dir(directory)
sys.path.append(prevdir+'text_features')
print(pr... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/video_features/helpers/cut_video.py | features/video_features/helpers/cut_video.py | import os, librosa, math, shutil
def cut_video(video, splitlength):
audio=video[0:-4]+'.wav'
foldername=video[0:-4]
os.system('ffmpeg -i %s %s'%(video, audio))
y, sr=librosa.core.load(audio)
duration=librosa.core.get_duration(y,sr)
splits=math.floor(duration/10)
count=0
curdir=os.getcwd()
try:
os.mkdir(fo... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/glove_features.py | features/text_features/glove_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/blabla_features.py | features/text_features/blabla_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/grammar_features.py | features/text_features/grammar_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/fast_features.py | features/text_features/fast_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/textacy_features.py | features/text_features/textacy_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/nltk_features.py | features/text_features/nltk_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/text2_features.py | features/text_features/text2_features.py | import nltk
nltk.download('universal_tagset')
from nltk.tokenize import RegexpTokenizer, word_tokenize
from nltk.tokenize import word_tokenize
from nltk import FreqDist
import numpy as np
import math
def filler_ratio(s, tokens = None):
if tokens == None:
tokens = word_tokenize(s)
tokenizer = RegexpTokeni... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/spacy_features.py | features/text_features/spacy_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/text_features.py | features/text_features/text_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/bert_features.py | features/text_features/bert_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/w2v_features.py | features/text_features/w2v_features.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/featurize.py | features/text_features/featurize.py | '''
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... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/helpers/transcribe.py | features/text_features/helpers/transcribe.py | '''
================================================
## VOICEBOOK REPOSITORY ##
================================================
repository name: voicebook
repository version: 1.0
repository link: https://github.com/jim-schwoebel/voicebook
author: Jim Schwoebel
author contact: js@neur... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/helpers/blabla/setup.py | features/text_features/helpers/blabla/setup.py | from setuptools import setup
setup(
name="blabla",
version="0.2.2",
description="Novoic linguistics feature extraction package.",
url="http://github.com/novoic/BlaBla",
author="Abhishek Shivkumar",
author_email="abhishek@novoic.com",
license="GPL-3.0",
packages=[
"blabla",
... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/helpers/blabla/docs/conf.py | features/text_features/helpers/blabla/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | false |
jim-schwoebel/allie | https://github.com/jim-schwoebel/allie/blob/b89f1403f63033ad406d0606b7c7a45000b43481/features/text_features/helpers/blabla/blabla/document_engine.py | features/text_features/helpers/blabla/blabla/document_engine.py | import traceback
from blabla.sentence_aggregators.phonetic_and_phonological_feature_aggregator import (
phonetic_and_phonological_feature_processor,
)
from blabla.sentence_aggregators.lexico_semantic_fearture_aggregator import (
lexico_semantic_feature_processor,
)
from blabla.sentence_aggregators.morpho_synta... | python | Apache-2.0 | b89f1403f63033ad406d0606b7c7a45000b43481 | 2026-01-05T07:09:07.495102Z | true |
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