mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-16 00:13:07 +00:00
Brandon Thomas
50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from omegaconf import OmegaConf
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from pytorch_lightning import seed_everything
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from nemo.collections.asr.models import ClusteringDiarizer
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from nemo.core.config import hydra_runner
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from nemo.utils import logging
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"""
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This script demonstrates how to use run speaker diarization.
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Usage:
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python speaker_diarize.py \
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diarizer.paths2audio_files=<either list of audio file paths or file containing paths to audio files> \
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diarizer.path2groundtruth_rttm_files=<(Optional) either list of rttm file paths or file containing paths to rttm files> \
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diarizer.vad.model_path="vad_telephony_marblenet" \
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diarizer.vad.threshold=0.7 \
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diarizer.speaker_embeddings.model_path="speakerverification_speakernet" \
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diarizer.out_dir="demo"
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Check out whole parameters in ./conf/speaker_diarization.yaml and their meanings.
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For details, have a look at <NeMo_git_root>/tutorials/speaker_recognition/Speaker_Diarization_Inference.ipynb
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"""
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seed_everything(42)
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@hydra_runner(config_path="conf", config_name="speaker_diarization.yaml")
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def main(cfg):
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logging.info(f'Hydra config: {OmegaConf.to_yaml(cfg)}')
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sd_model = ClusteringDiarizer(cfg=cfg)
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sd_model.diarize()
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if __name__ == '__main__':
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main()
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