| import tqdm |
| import argparse |
| import pandas as pd |
| import os |
| import sys |
|
|
| dir_path = os.path.dirname(os.path.realpath(__file__)) |
| parent_dir_path = os.path.abspath(os.path.join(dir_path, os.pardir)) |
| sys.path.insert(0, parent_dir_path) |
| from pathlib import Path |
| import os |
| import tqdm |
| import argparse |
| import pandas as pd |
| import sentencepiece as spm |
|
|
| from pathlib import Path |
| from tempfile import NamedTemporaryFile |
| import sys |
| import os |
| import re |
|
|
| from examples.speech_to_text.data_utils import ( |
| load_df_from_tsv, |
| save_df_to_tsv, |
| gen_vocab, |
| ) |
| from examples.speech_synthesis.data_utils import ipa_phonemize |
|
|
| from examples.speech_to_text.data_utils import ( |
| load_df_from_tsv, |
| save_df_to_tsv, |
| gen_config_yaml, |
| ) |
| from fairseq.data.audio.data_cfg import S2SDataConfig |
|
|
| MANIFEST_COLUMNS = [ |
| "id", |
| "audio", |
| "n_frames", |
| "src_text", |
| "tgt_text", |
| "speaker", |
| "src_lang", |
| "tgt_lang", |
| ] |
| LANG_TAG_TEMPLATE = "<lang:{}>" |
|
|
|
|
| def process(args): |
| s2st_tsv_dir = Path(args.s2st_tsv_dir) |
| s2tt_tsv_dir = Path(args.s2tt_mtl_tsv_dir) |
| s2tt_tsv_dir.mkdir(exist_ok=True) |
| train_text = [] |
| for split in ["train", "dev", "test"]: |
| manifest = {c: [] for c in MANIFEST_COLUMNS} |
| df = load_df_from_tsv(s2st_tsv_dir / f"{split}.tsv") |
| data = list(df.T.to_dict().values()) |
| for item in tqdm.tqdm(data): |
| item["src_text"] = re.sub(r"[^\w\s]", "", item["src_text"].lower()) |
| manifest["id"].append(item["id"]) |
| manifest["audio"].append(item["src_audio"]) |
| manifest["n_frames"].append(item["src_n_frames"]) |
| manifest["src_text"].append(item["src_text"]) |
| manifest["tgt_text"].append(item["tgt_text"]) |
| manifest["speaker"].append("None") |
| manifest["src_lang"].append(args.src_lang) |
| manifest["tgt_lang"].append(args.tgt_lang) |
| if split == "train": |
| train_text.append(item["src_text"]) |
| train_text.append(item["tgt_text"]) |
| df = pd.DataFrame.from_dict(manifest) |
| save_df_to_tsv(df, s2tt_tsv_dir / f"{split}.tsv") |
|
|
| with NamedTemporaryFile(mode="w") as f: |
| for t in train_text: |
| f.write(t + "\n") |
| gen_vocab( |
| Path(f.name), |
| Path(s2tt_tsv_dir).absolute() / f"spm_unigram_joint", |
| "unigram", |
| args.vocab_size, |
| special_symbols=[ |
| LANG_TAG_TEMPLATE.format(args.tgt_lang), |
| LANG_TAG_TEMPLATE.format(args.src_lang), |
| ], |
| ) |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--s2st-tsv-dir") |
| parser.add_argument("--s2tt-mtl-tsv-dir") |
| parser.add_argument("--src-lang") |
| parser.add_argument("--tgt-lang") |
| parser.add_argument("--vocab-size") |
| args = parser.parse_args() |
| process(args) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
