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`ValueError` when trying to import pretrained model.
**Steps/Code to reproduce bug**
```python
import nemo.collections.asr as nemo_asr
model = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name="QuartzNet15x5Base-En")
[NeMo I 2021-07-06 22:51:41 cloud:66] Downloading from: https:... | {
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} | - Speed up on eigen decomposition by using GPU.
- Speed up on NME analysis by subsampling.
- Fixed the diarization evaluation parameter (no score collar: from 0.25 s to 0.5 s) | {
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I am using the02_Online_ASR_Microphone_Demo.ipynb notebook. Followed all the steps but in the end, I am getting ERROR: No audio input device found. Colab has microphone access through the browser. Any fix for this?
Thanks | {
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I'm doing a training with 10_ASR_CTC_Language_Finetuning, I was wondering if you would have a reference of these settings, 
which values would be better for a training in Portuguese?
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This will help in finding the best set of paramters when training using Nemo on different sorts of data.
This can make the training more straightforward and can be of an advantage compared t... | {
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I am trying to finetune the Citrinet_1024 nemo model first on 50K chunks of the Indian accent English-language dataset using 1 gpu.
Since [here](https://github.com/NVIDIA/NeMo/tree/main/examples/asr/conf/citrinet) is no config file for citrinet_1024. So I changed the filters 512 to 1024, set the dropout to 0.01... | {
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} | * Brought in the needed changes from Vahid's earlier PR: https://github.com/NVIDIA/NeMo/pull/2359/files
* Tested conversion with scripts/export/convasr_to_single_onnx.py
* Tested the converted large, medium and small models with dev-clean and WER is very close (within 0.01%) of correspondiong .nemo models
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Hi,
Today after I have installed NeMo, I have tried the ASR both in English and Chinese -- it all works very well!!
Also I did a quick tts test on the English based on following setting -- it works!
# Download and load the pretrained tacotron2 model
spec_generator = SpectrogramGenerator... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2437 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2437/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2437/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2437/events | https://github.com/NVIDIA/NeMo/pull/2437 | 936,033,470 | MDExOlB1bGxSZXF1ZXN0NjgyODUyNzc3 | 2,437 | Merge r1.1 bugfixes to main. Update dep versions. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2436 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2436/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2436/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2436/events | https://github.com/NVIDIA/NeMo/issues/2436 | 936,003,216 | MDU6SXNzdWU5MzYwMDMyMTY= | 2,436 | Model QuartzNet15x5Base-Zh was not found | {
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Hi,
I am new to NeMo. After I have installed the NeMo in my dGPU laptop, I have written a simple test to test the ASR.
1. first I have test the .wav file in English ("Where is the bus station?")
quartznet = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name="QuartzNet15x5Base-En... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2435 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2435/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2435/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2435/events | https://github.com/NVIDIA/NeMo/pull/2435 | 935,915,720 | MDExOlB1bGxSZXF1ZXN0NjgyNzUxOTI0 | 2,435 | add uperbound on PTL version | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2434 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2434/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2434/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2434/events | https://github.com/NVIDIA/NeMo/issues/2434 | 935,449,234 | MDU6SXNzdWU5MzU0NDkyMzQ= | 2,434 | Error: Cannot resolve schedulerDictConfig when run VAD training tutorial | {
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} | null | null | null | Hi teams, I tried to run this notebook https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/06_Voice_Activiy_Detection.ipynb
However, when I ran `trainer.fit(vad_model)`. It returns following errors
`---------------------------------------------------------------------------
ValueError ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2433 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2433/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2433/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2433/events | https://github.com/NVIDIA/NeMo/issues/2433 | 935,397,730 | MDU6SXNzdWU5MzUzOTc3MzA= | 2,433 | Does Nemo or Jarvis support Hot words with boost in their current version? | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2432 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2432/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2432/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2432/events | https://github.com/NVIDIA/NeMo/issues/2432 | 935,338,299 | MDU6SXNzdWU5MzUzMzgyOTk= | 2,432 | Fail to load SpeakerNet when inference Speaker Diarization | {
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I trained SpeakerNet with my own dataset and got checkpoint to test speaker diarization. I tried both configs of SpeakerNet in here.
[Configs](https://github.com/NVIDIA/NeMo/tree/main/examples/speaker_recognition/conf)
Because pytorch lightning trainer save checkpoint as .ckpt format so i usin... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2431 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2431/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2431/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2431/events | https://github.com/NVIDIA/NeMo/pull/2431 | 935,208,212 | MDExOlB1bGxSZXF1ZXN0NjgyMTYyMjAx | 2,431 | Update container version to 21.06 | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2430 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2430/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2430/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2430/events | https://github.com/NVIDIA/NeMo/pull/2430 | 935,177,726 | MDExOlB1bGxSZXF1ZXN0NjgyMTM2MTkz | 2,430 | Update deployment instructions | {
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I am trying to fine-tune **stt_en_conformer_ctc_large** model using the following:
`asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="stt_en_conformer_ctc_large")`
Then I set the training params:
```
# not working:
from omegaconf import OmegaConf, open_dict
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Similar to https://github.com/pytorch/pytorch/issues/8637, ModelPT class adds training_step to its parameters [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/core/classes/modelPT.py#L159). Because of that, when training with 'dp' accelerator workers call the same instanced function instead of... | {
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} | # Bugfix
- Onnx is at 1.9, onnxruntime is at 1.8
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | # Changelog
- ONNX version updated for notebooks
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} | null | null | null | The CTC Segmentation to split the audio files and its transcripts, is not working with German audios. I followed the tutorial on COLAB. Is there any other model to be used for German language? | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2418 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2418/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2418/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2418/events | https://github.com/NVIDIA/NeMo/pull/2418 | 932,010,383 | MDExOlB1bGxSZXF1ZXN0Njc5NDE5NjUy | 2,418 | Parallelize CPU-GPU unittests | {
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} | # Changelog
- Parallelize CPU and GPU unit tests
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2417 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2417/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2417/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2417/events | https://github.com/NVIDIA/NeMo/pull/2417 | 931,879,662 | MDExOlB1bGxSZXF1ZXN0Njc5MzA0NzM1 | 2,417 | [BUGFIX] Megatron in NMT was setting vocab_file to None | {
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} | Makes vocab_file configurable with Megatron encoders in NeMo NMT. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2416 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2416/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2416/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2416/events | https://github.com/NVIDIA/NeMo/pull/2416 | 931,818,433 | MDExOlB1bGxSZXF1ZXN0Njc5MjUyOTgy | 2,416 | Link updates in docs and notebooks and typo fix | {
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} | Typo for Voice Activi**t**y Detection notebooks/links fix
Update links in docs for branches to **stable**
Update links in notebooks for branches to **stable**
Will submit a PR to update links in **main** branch to main once this PR has been merged to r1.1.0 and main
Please make sure to update **stable** before r... | {
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} | Added code for training/evaluating a text normalization system which consists of:
(1) A tagger - for identifying semiotic classes in the input
(2) A decoder - for decoding the spans of semiotic classes into spoken form.
@yzhang123 @ekmb | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2414 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2414/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2414/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2414/events | https://github.com/NVIDIA/NeMo/issues/2414 | 931,623,802 | MDU6SXNzdWU5MzE2MjM4MDI= | 2,414 | Using the beamsearch with LM | {
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} | null | null | null | Hello everyone,
I'm testing the Offline_ASR in Colab, at the beamsearch part I getting some results, as expected. But I just need the first
hypothesis, so I won't need to process the other hypothesis. Have any way to do this? A way to just process one hypothesis. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2413 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2413/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2413/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2413/events | https://github.com/NVIDIA/NeMo/issues/2413 | 931,536,384 | MDU6SXNzdWU5MzE1MzYzODQ= | 2,413 | Run Offline_ASR (python notebook) decode with a GPU | {
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I'm using the Offline_ASR notebook testing some large and small values for width, alpha and beta in 'beamsearch', all is correct and returning good results, but needs so much time to return those results. This script is running in Colab.
Have some way to run this notebook or only the beamsearch part with a G... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2412 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2412/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2412/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2412/events | https://github.com/NVIDIA/NeMo/issues/2412 | 931,526,604 | MDU6SXNzdWU5MzE1MjY2MDQ= | 2,412 | Run multiple model inference on a single GPU concurrently | {
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I have a queue of audio files waiting to be transcribed. when I run the citrinet model on them I see there's still free memory on the gpu hence my question - is there a way and how, to run multiple nemo models (can be all citrinet for example, but also others) concurrently on a single gpu?
btw u... | {
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The data preparation script `run_sample.sh` errors out pretty frequently, caused by opening too many files at the same time and hitting the process file limit. This seems to arise from the 'prepare_data.py' script which is called
**Steps/Code to reproduce bug**
(This seems to stem from the... | {
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I found this training script here (https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/language_modeling/transformer_lm.py), but I did not know how to use it? can you ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2408 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2408/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2408/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2408/events | https://github.com/NVIDIA/NeMo/pull/2408 | 930,360,959 | MDExOlB1bGxSZXF1ZXN0Njc4MDY2ODk2 | 2,408 | fixed minor errors in docs and filter_langs_nmt.py | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2407 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2407/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2407/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2407/events | https://github.com/NVIDIA/NeMo/pull/2407 | 930,318,367 | MDExOlB1bGxSZXF1ZXN0Njc4MDMzNzgx | 2,407 | Merge r1.1 bugfixes into main | {
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} | After cutting a release branch, we merge bugfixes back into main. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2406 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2406/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2406/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2406/events | https://github.com/NVIDIA/NeMo/issues/2406 | 930,213,486 | MDU6SXNzdWU5MzAyMTM0ODY= | 2,406 | Wav2Vec2 Fine-tuning Tutorial | {
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As you currently don't have a tutorial for training wav2vec2 #2342, I tried to create a new yaml file to train wav2vec2.
However, I didn't succeed and I need your guidance and help.
I have created a Colab example that replicate my experiment here:
https://colab.research.google.com/drive/1kJQA0wm7EVLGsDlZmhC... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2405 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2405/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2405/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2405/events | https://github.com/NVIDIA/NeMo/issues/2405 | 930,189,873 | MDU6SXNzdWU5MzAxODk4NzM= | 2,405 | Fine-tune Citrinet config file | {
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My question is: which configuration file should I modify for fine-tuning:
option 1: the original config file of the model obtained from **asr_model.cfg**
option 2: download **config_bpe** [here ](https://github.com/NVIDIA/Ne... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2404 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2404/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2404/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2404/events | https://github.com/NVIDIA/NeMo/issues/2404 | 929,873,366 | MDU6SXNzdWU5Mjk4NzMzNjY= | 2,404 | No pad_token,eos_token,sep_token,cls_token in SentencePieceTokenizer | {
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Hi I find actually no pad_token,eos_token,sep_token,cls_token in SentencePieceTokenizer's property. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2403 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2403/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2403/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2403/events | https://github.com/NVIDIA/NeMo/pull/2403 | 929,873,264 | MDExOlB1bGxSZXF1ZXN0Njc3NjYwNTY0 | 2,403 | remove accelerator=DDP in tutorial notebooks to avoid errors. | {
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} | Signed-off-by: Hoo Chang Shin <hshin@nvidia.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2402 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2402/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2402/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2402/events | https://github.com/NVIDIA/NeMo/pull/2402 | 929,675,711 | MDExOlB1bGxSZXF1ZXN0Njc3NDkxMDk2 | 2,402 | Correct typos and issues with notebooks | {
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} | # Bugfix
- Correct OmegaConf issue with primer notebook
- Correct typo in ASR notebook | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2401 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2401/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2401/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2401/events | https://github.com/NVIDIA/NeMo/pull/2401 | 929,596,118 | MDExOlB1bGxSZXF1ZXN0Njc3NDIzMjYy | 2,401 | Add blossom-ci.yml | {
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} | Adding blossom workflow for testing blossom CI. | {
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} | # Bugfix
- Fix a bug in adaptive time masking where the mask start index could begin in a padded region, therefore making the mask useless (ASR losses dont access masked sections when computing loss).
- In effect, augmentation was reduced. | {
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Signed-off-by: Oktai Tatanov <oktai.tatanov@gmail.com> | {
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} | # Changelog
- Correct spelling mistakes
- Correct branch of notebook
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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# Summary
The bottleneck class (MTBottleneckModel) supports two architectures:
* No bottleneck: model_type=seq2seq, the usual NMT mdoel.
* Fixed-size bottleneck: model_type in [seq2seq-b... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2387 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2387/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2387/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2387/events | https://github.com/NVIDIA/NeMo/issues/2387 | 927,168,337 | MDU6SXNzdWU5MjcxNjgzMzc= | 2,387 | Gradient overflow | {
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} | null | null | null | **Describe the bug**
I'm receiving these warnings and errors when I'm training Quartznet using spanish dataset at A100:
***Warnings:***
- Could not import torchaudio. Some features might not work. warnings.warn('Could not import torchaudio. Some features might not work.')libibverbs:
- Warning: no userspace de... | {
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} | null | null | null | I want to finetune pre-trained citrinet-1024 for my **8Khz** data set. What steps should I follow?
I did these steps
1) tokenizer traininig with my train data
But then
2) asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="stt_en_citrinet_1024") does not see my config file and gives error
3... | {
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} | null | null | null | **Describe the bug**
Given the default configuration of fastspeech2 and HifiGAN, their implemented learning rates deviate severely from what's reported in their respective original papers.
**Steps/Code to reproduce bug**
Preprocess LJSpeech as specified by the official NeMo example,
python fastspeech2.py (or... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2381 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2381/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2381/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2381/events | https://github.com/NVIDIA/NeMo/pull/2381 | 926,725,845 | MDExOlB1bGxSZXF1ZXN0Njc0OTkxODMy | 2,381 | Update ASR scripts for tokenizer building and tarred dataset building | {
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} | # Changelog
- Update docker container to nemo:1.0.1
- Add Citrinet 1024 Gamma 0.25 model card for Mandarin to CTC char models
- Update tokenizer scripts to support adding bos, eos and pad tokens to SentencePiece tokenizers via `--spe_bos`, `--spe_eos` and `--spe_pad` flags.
- Update dataset building script to alwa... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2380 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2380/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2380/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2380/events | https://github.com/NVIDIA/NeMo/pull/2380 | 926,664,630 | MDExOlB1bGxSZXF1ZXN0Njc0OTQwNTEz | 2,380 | [BUGFIX] NMT Multi-node was incorrectly computing num_replicas | {
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} | We need to instantiate the `NLPDDPPlugin` with the `num_nodes` gotten from the trainer config. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2379 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2379/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2379/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2379/events | https://github.com/NVIDIA/NeMo/pull/2379 | 926,628,516 | MDExOlB1bGxSZXF1ZXN0Njc0OTA5MDc3 | 2,379 | ListConfig for training, right to left models, noisy channel re-ranking and ensembling for NMT | {
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} | This PR implements the following features
1. ListConfig for training NMT datasets that aren't restricted to multilingual training. Implication - users can specify multiple training text/tar files and sample from different sources with probabilities.
For example,
```
python examples/nlp/machine_translation/enc... | {
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} | Need to update notebook branch and Jenkinsfile for 1.1.0 testing.
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https://api.github.com/repos/NVIDIA/NeMo/issues/2377 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2377/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2377/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2377/events | https://github.com/NVIDIA/NeMo/issues/2377 | 926,155,193 | MDU6SXNzdWU5MjYxNTUxOTM= | 2,377 | examples/asr/quantization/speech_to_text_quant_infer.py run error | {
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nvcr.io/nvidia/nemo:1.0.0rc1
command:
python speech_to_text_quant_infer.py --asr_model ./QuartzNet15x5Base-En-max-16.nemo --dataset ./test.json --sensitivity --onnx
error:
W0621 12:00:53.572198 140041427298112 tensor_quantizer.py:280] Use Pytorch's native experimental fake quantization.
[NeMo W ... | {
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} | null | null | null | Hello, I tried to run a BERT pre-training in a distributed fashion with [Ray](https://github.com/ray-project), more specifically using [ray_lightning](https://github.com/ray-project/ray_lightning) as a plugin. Apparently, the BERTLMModel cannot be serialized (stack trace below)
```
Traceback (most recent call last):
... | {
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Can I use Persian Multiple speaker audio datasets for fine-tuning QuartzNet15*5? Will be the WER low as I fine-tune it with a single speaker dataset?
Thanks
**Environment overview**
- Environment location: Google Colab
- Method of NeMo install: !pip install nemo_toolkit[asr]
- NeMo version: 1.0.0
- Lea... | {
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} | # Changelog
- Adds Numpy + CPU + Numba CUDA support for FastEmit regularization from the paper [FastEmit: Low-latency Streaming ASR with Sequence-level Emission Regularization](https://arxiv.org/abs/2010.11148)
# Usage
```yaml
model: # RNNT Model config
...
loss:
loss_name: "warprnnt_numba"
war... | {
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} | * speech_to_text_buffered_infer.py supports inference on long audio files by running inference on smaller chunks of audio and them merging the tokens for final transcription.
* This version only supports EncDecCTCModelBPE with AudioMelSpectrogramProcessor as the preprocessor
* Feature normalization is done on each b... | {
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I have successfully trained VAD according to your tutorial with my background data set. However, when I start training VAD with a background sample length of 0.1s, I get an error. Please tell me which parameter needs to be changed to avoid this.
`trainer.fit(vad_model)`
```
LOCAL_RANK: 0 - CUDA_VISIBL... | {
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I was able to run the https://colab.research.google.com/github/NVIDIA/NeMo/blob/main/tutorials/asr/10_ASR_CTC_Language_Finetuning.ipynb script in Colab with no problems. However, due to disk and GPU limitations, I took this script and ran it in my environment using JupyterLab.
When starting the training, exactl... | {
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} | # Changelog
- Add Citrinet Gamm 0.25 model card info
- Remove older models that are deprecated due to better checkpoints being availabls
- stt_zh_quartznet_15x5
- Cleanup duplicated documentation for ASR notes | {
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} | null | null | null | **Hi, how are you? will you be able to help me with this question...**
About the "Speaker Recognition Verification", after all the training process you give us the option to extract the Embeddings from the speakers, but we would like to know if we can extract the speaker ID, we also look at your other scripts the ones... | {
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} | null | null | null | Hi,
I'm using the container https://ngc.nvidia.com/catalog/containers/nvidia:nemo_asr_app_img and running the step by step from the notebook 'English to Spanish Cross Language Finetuning'. I did the training and everything works perfectly.
At the end of training as a result we have checkpoints that can be used for ... | {
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} | # Bugfix
- Change colab link to new notebook.
- TODO: Change link to next release version from `main`
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | This PR adds:
* a straightforward implementation of unicode encoding & decoding from [ByT5](https://arxiv.org/abs/2105.13626)
* a very bare-bones text processor for use with this tokenizer that can support any language.
Usage:
To enable this, add the following lines to your nemo launch script:
```
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An example of this error is in the notebook "Speaker Diarization Inference":
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- added support for roman numbers up to 1000 (audio-based normalization only)
- parallel normalization of manifests
- bug fixes and pre/post-processing updates to improve normalization coverage | {
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I get this error wh... | {
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My dataset is Vietnamese telephony conversation, 15 hours with 8 hours of speech and 7 hours of noise. I got accuracy 95% on my test set.
The format of ... | {
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I am trying to transcribe an audio file with following ground truth:
**in the late 1980s switzerland witnessed a huge increase**
and getting the following prediction by Citrinet:
**in the late one thousand nine hundred eighty seconds switzerland witnessed a huge increase**
**Steps/Code to re... | {
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Is posible to use .ckpt model in Config file.
Many thanks. | {
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} | Hydra-core version 1.1.0 was released on 11th June 2021, and it requires OmegaConf == 2.1.\*, while Nemo requires OmegaConf >=2.0.5 & <2.1.*. Therefore, the existing tutorial notebooks( can be found [here](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/starthere/tutorials.html), on importing the mod... | {
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} | # Changelog
- Adds tutorial to fine-tune an ASR CTC model onto another language (MCV Japanese for demo)
- Adds documentation to point user to finetuning via ASR tutorials
- Update link color for visited links in NeMo Docs | {
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`punctuation_model = PunctuationCapitalizationModel.from_pretrained("punctuation_en_bert")`
I get this error:
```
ConfigAttributeError Traceback (most recent call last)
<ipython-input-2-e68f34283879> in <module>()
15 import time
16 translate_model = MTEn... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2342 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2342/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2342/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2342/events | https://github.com/NVIDIA/NeMo/issues/2342 | 918,572,801 | MDU6SXNzdWU5MTg1NzI4MDE= | 2,342 | Wav2Vec2 Fine-tuning Tutorial | {
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I was able only to find the pre-training script.
Could you please share an example for fine-tuning wav2vec2?
https://github.com/NVIDIA/NeMo/blob/ee480c1a7905a6488ede29c9d892b6be3038759f/examples/asr/experimental/wav2vec/wav2vec_pretrain.py
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https://api.github.com/repos/NVIDIA/NeMo/issues/2339 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2339/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2339/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2339/events | https://github.com/NVIDIA/NeMo/issues/2339 | 918,450,163 | MDU6SXNzdWU5MTg0NTAxNjM= | 2,339 | Automatic audio resampling on the fly | {
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Assuming I have a dataset that consists of different sampling rage "32k, 16k, and 8k", Can Nemo automatically resample them during training into the model-specific sample rate defined in the YAML file? | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2338 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2338/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2338/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2338/events | https://github.com/NVIDIA/NeMo/pull/2338 | 918,278,953 | MDExOlB1bGxSZXF1ZXN0NjY3NzI0NDUx | 2,338 | Update notebooks to 1.0.2 release | {
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} | # Changelog
- Update all notebooks and docs to refer to r1.0.2 release
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2337 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2337/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2337/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2337/events | https://github.com/NVIDIA/NeMo/pull/2337 | 917,995,378 | MDExOlB1bGxSZXF1ZXN0NjY3NDc1NjY0 | 2,337 | [BUGFIX] Add upper bound to hydra for 1.0.x | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2336 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2336/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2336/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2336/events | https://github.com/NVIDIA/NeMo/pull/2336 | 917,994,245 | MDExOlB1bGxSZXF1ZXN0NjY3NDc0NjI3 | 2,336 | Update ranges for omegaconf and hydra | {
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} | # Bugfix
- Updates ranges of hydra and omegaconf to support latest release
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2334 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2334/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2334/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2334/events | https://github.com/NVIDIA/NeMo/issues/2334 | 917,095,147 | MDU6SXNzdWU5MTcwOTUxNDc= | 2,334 | FineTune ASR with freeze encoder | {
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I try FineTune ASR with freeze encoder on Russian language.
I am taking the parameters of the optimizer, learning rate from the this paper
https://arxiv.org/pdf/2005.04290.pdf and i set warmup_steps the value to 2000, but when training the model, the loss value is "buried", and WER is in one.
What actio... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2333 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2333/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2333/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2333/events | https://github.com/NVIDIA/NeMo/pull/2333 | 916,773,686 | MDExOlB1bGxSZXF1ZXN0NjY2NDAxMzA4 | 2,333 | comment out if statement for checkpoint_file | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2332 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2332/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2332/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2332/events | https://github.com/NVIDIA/NeMo/pull/2332 | 916,760,220 | MDExOlB1bGxSZXF1ZXN0NjY2Mzg5NDI1 | 2,332 | update main GH README | {
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} | Added a quick list of main features with links to docs.
Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2329 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2329/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2329/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2329/events | https://github.com/NVIDIA/NeMo/issues/2329 | 916,677,391 | MDU6SXNzdWU5MTY2NzczOTE= | 2,329 | speech_to_text.py doesn't work | {
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I am trying to run the "speech_to_text.py " but it fails and gives the following error:
```
File "speech_to_text.py", line 88, in main
asr_model.maybe_init_from_pretrained_checkpoint(cfg)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 948, in __getattr... | {
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I'm trying to train a NMT model using Nemo on my machine. I followed the instructions from the [documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/machine_translation.html) using the example script and the default configuration file. This runs perfectly on colab, but whe... | {
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