Download preprocess_scripts/data_utils.py from echodict/StreamSpeech: direct link, hf CLI and curl.
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https://huggingface.co/datasets/echodict/StreamSpeech/resolve/main/preprocess_scripts/data_utils.py
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hf download hf://datasets/echodict/StreamSpeech/preprocess_scripts/data_utils.py
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2.88 kB
| # 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. | |
| from pathlib import Path | |
| from typing import List, Optional | |
| from examples.speech_to_text.data_utils import S2TDataConfigWriter | |
| def gen_config_yaml( | |
| manifest_root: Path, | |
| yaml_filename: str = "config.yaml", | |
| specaugment_policy: Optional[str] = "lb", | |
| # feature_transform: Optional[List[str]] = None, | |
| cmvn_type: str = "utterance", | |
| gcmvn_path: Optional[Path] = None, | |
| input_channels: Optional[int] = 1, | |
| input_feat_per_channel: Optional[int] = 80, | |
| audio_root: str = "", | |
| vocoder_type: Optional[str] = None, | |
| vocoder_checkpoint: Optional[str] = None, | |
| vocoder_cfg: Optional[str] = None, | |
| extra=None, | |
| ): | |
| manifest_root = manifest_root.absolute() | |
| writer = S2TDataConfigWriter(manifest_root / yaml_filename) | |
| if input_channels is not None: | |
| writer.set_input_channels(input_channels) | |
| if input_feat_per_channel is not None: | |
| writer.set_input_feat_per_channel(input_feat_per_channel) | |
| specaugment_setters = { | |
| "lb": writer.set_specaugment_lb_policy, | |
| "ld": writer.set_specaugment_ld_policy, | |
| "sm": writer.set_specaugment_sm_policy, | |
| "ss": writer.set_specaugment_ss_policy, | |
| } | |
| specaugment_setter = specaugment_setters.get(specaugment_policy, None) | |
| if specaugment_setter is not None: | |
| specaugment_setter() | |
| if cmvn_type not in ["global", "utterance"]: | |
| raise NotImplementedError | |
| if specaugment_policy is not None: | |
| writer.set_feature_transforms("_train", [f"{cmvn_type}_cmvn", "specaugment"]) | |
| writer.set_feature_transforms("*", [f"{cmvn_type}_cmvn"]) | |
| if cmvn_type == "global": | |
| if gcmvn_path is None: | |
| raise ValueError("Please provide path of global cmvn file.") | |
| else: | |
| writer.set_global_cmvn(gcmvn_path.as_posix()) | |
| if len(audio_root) > 0: | |
| writer.set_audio_root(audio_root) | |
| if ( | |
| vocoder_type is not None | |
| and vocoder_checkpoint is not None | |
| and vocoder_cfg is not None | |
| ): | |
| writer.set_extra( | |
| { | |
| "vocoder": { | |
| "type": vocoder_type, | |
| "config": vocoder_cfg, | |
| "checkpoint": vocoder_checkpoint, | |
| } | |
| } | |
| ) | |
| if extra is not None: | |
| writer.set_extra(extra) | |
| writer.flush() | |
| def load_units(in_file): | |
| out = {} | |
| with open(in_file) as f: | |
| for line in f: | |
| sample_id, units = line.strip().split("|", 1) | |
| out[sample_id] = units.split() | |
| return out | |
| def process_units(units, reduce=False): | |
| if not reduce: | |
| return units | |
| out = [u for i, u in enumerate(units) if i == 0 or u != units[i - 1]] | |
| return out | |