scripts/dataset_processing/speaker_tasks/get_ami_data.py

# Copyright (c) 2022, NVIDIA CORPORATION.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Download the AMI test dataset used to evaluate Speaker Diarization
# More information here: https://groups.inf.ed.ac.uk/ami/corpus/
# USAGE: python get_ami_data.py
import argparse
import os

from nemo.collections.asr.parts.utils.manifest_utils import create_manifest

rttm_url = "https://raw.githubusercontent.com/BUTSpeechFIT/AMI-diarization-setup/main/only_words/rttms/{}/{}.rttm"
uem_url = "https://raw.githubusercontent.com/BUTSpeechFIT/AMI-diarization-setup/main/uems/{}/{}.uem"
list_url = "https://raw.githubusercontent.com/BUTSpeechFIT/AMI-diarization-setup/main/lists/{}.meetings.txt"


audio_types = ['Mix-Headset', 'Array1-01']

# these two IDs in the train set are missing download links for Array1-01.
# We exclude them as a result.
not_found_ids = ['IS1007d', 'IS1003b']

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Download the AMI Corpus Dataset for Speaker Diarization")
    parser.add_argument(
        "--test_manifest_filepath",
        help="path to output test manifest file",
        type=str,
        default='AMI_test_manifest.json',
    )
    parser.add_argument(
        "--dev_manifest_filepath", help="path to output dev manifest file", type=str, default='AMI_dev_manifest.json',
    )
    parser.add_argument(
        "--train_manifest_filepath",
        help="path to output train manifest file",
        type=str,
        default='AMI_train_manifest.json',
    )
    parser.add_argument("--data_root", help="path to output data directory", type=str, default="ami_dataset")
    args = parser.parse_args()

    data_path = os.path.abspath(args.data_root)
    os.makedirs(data_path, exist_ok=True)

    for manifest_path, split in (
        (args.test_manifest_filepath, 'test'),
        (args.dev_manifest_filepath, 'dev'),
        (args.train_manifest_filepath, 'train'),
    ):
        split_path = os.path.join(data_path, split)
        audio_path = os.path.join(split_path, "audio")
        os.makedirs(split_path, exist_ok=True)
        rttm_path = os.path.join(split_path, "rttm")
        uem_path = os.path.join(split_path, "uem")

        os.system(f"wget -P {split_path} {list_url.format(split)}")
        with open(os.path.join(split_path, f"{split}.meetings.txt")) as f:
            ids = f.read().strip().split('\n')
        for id in [file_id for file_id in ids if file_id not in not_found_ids]:
            for audio_type in audio_types:
                audio_type_path = os.path.join(audio_path, audio_type)
                os.makedirs(audio_type_path, exist_ok=True)
                os.system(
                    f"wget -P {audio_type_path} https://groups.inf.ed.ac.uk/ami/AMICorpusMirror//amicorpus/{id}/audio/{id}.{audio_type}.wav"
                )
            rttm_download = rttm_url.format(split, id)
            os.system(f"wget -P {rttm_path} {rttm_download}")
            uem_download = uem_url.format(split, id)
            os.system(f"wget -P {uem_path} {uem_download}")

        rttm_files_path = os.path.join(split_path, 'rttm_files.txt')
        with open(rttm_files_path, 'w') as f:
            f.write('\n'.join(os.path.join(rttm_path, p) for p in os.listdir(rttm_path)))
        uem_files_path = os.path.join(split_path, 'uem_files.txt')
        with open(uem_files_path, 'w') as f:
            f.write('\n'.join(os.path.join(uem_path, p) for p in os.listdir(uem_path)))
        for audio_type in audio_types:
            audio_type_path = os.path.join(audio_path, audio_type)
            audio_files_path = os.path.join(split_path, f'audio_files_{audio_type}.txt')
            with open(audio_files_path, 'w') as f:
                f.write('\n'.join(os.path.join(audio_type_path, p) for p in os.listdir(audio_type_path)))
            audio_type_manifest_path = manifest_path.replace('.json', f'.{audio_type}.json')
            create_manifest(
                audio_files_path, audio_type_manifest_path, rttm_path=rttm_files_path, uem_path=uem_files_path
            )