Download fairseq/examples/speech_to_speech/preprocessing/prep_sn_data.py from echodict/StreamSpeech: direct link, hf CLI and curl.
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https://huggingface.co/datasets/echodict/StreamSpeech/resolve/main/fairseq/examples/speech_to_speech/preprocessing/prep_sn_data.py
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hf download hf://datasets/echodict/StreamSpeech/fairseq/examples/speech_to_speech/preprocessing/prep_sn_data.py
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curl -L -o prep_sn_data.py https://huggingface.co/datasets/echodict/StreamSpeech/resolve/main/fairseq/examples/speech_to_speech/preprocessing/prep_sn_data.py
2.74 kB
| #!/usr/bin/env python3 | |
| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| # | |
| # Adapted from examples/wav2vec/wav2vec_manifest.py | |
| """ | |
| Data preparation for the speech normalizer | |
| """ | |
| import argparse | |
| import glob | |
| import os | |
| import soundfile | |
| from examples.speech_to_speech.preprocessing.data_utils import load_units, process_units | |
| def process(args): | |
| assert ( | |
| args.for_inference or args.target_unit is not None | |
| ), "missing --target-unit or --for-inference" | |
| if not os.path.exists(args.output_dir): | |
| os.makedirs(args.output_dir) | |
| dir_path = os.path.realpath(args.audio_dir) | |
| search_path = os.path.join(dir_path, "**/*." + args.ext) | |
| if args.target_unit: | |
| unit_data = load_units(args.target_unit) | |
| with open(os.path.join(args.output_dir, f"{args.data_name}.tsv"), "w") as o_t, open( | |
| os.path.join(args.output_dir, f"{args.data_name}.unit"), "w" | |
| ) as o_u: | |
| print(dir_path, file=o_t) | |
| for fname in glob.iglob(search_path, recursive=True): | |
| file_path = os.path.realpath(fname) | |
| frames = soundfile.info(fname).frames | |
| print( | |
| "{}\t{}".format(os.path.relpath(file_path, dir_path), frames), file=o_t | |
| ) | |
| if args.for_inference: | |
| print("0", file=o_u) | |
| else: | |
| sample_id = os.path.basename(file_path)[: -len(args.ext) - 1] | |
| assert ( | |
| sample_id in unit_data | |
| ), f'{fname} does not have unit data in {args.target_unit}. Expecting sample_id "{sample_id}".' | |
| target_units = process_units(unit_data[sample_id], reduce=True) | |
| print(" ".join(target_units), file=o_u) | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--audio-dir", required=True, type=str, help="audio directory") | |
| parser.add_argument("--ext", default="flac", type=str, help="audio extension") | |
| parser.add_argument( | |
| "--data-name", | |
| required=True, | |
| type=str, | |
| help="dataset name", | |
| ) | |
| parser.add_argument( | |
| "--output-dir", required=True, type=str, help="output directory" | |
| ) | |
| parser.add_argument( | |
| "--for-inference", | |
| action="store_true", | |
| help="set this if preparing data for running inference with a speech normalizer", | |
| ) | |
| parser.add_argument( | |
| "--target-unit", | |
| default=None, | |
| type=str, | |
| help="a file containing unit sequences in the format: sample_id|u1 u2 ...", | |
| ) | |
| args = parser.parse_args() | |
| process(args) | |
| if __name__ == "__main__": | |
| main() | |