Update teric_asr_lab.py
Browse files- teric_asr_lab.py +9 -8
teric_asr_lab.py
CHANGED
@@ -28,7 +28,7 @@ from .release_stats import STATS
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_CITATION = """\
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-
@inproceedings{
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author = {Bateesa, T. and Wairagala, EP. },
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title = {Teric Lab: A Massively-Multilingual Speech Corpus},
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}
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@@ -43,7 +43,7 @@ _BASE_URL = "https://huggingface.co/datasets/Tobius/teric_asr_lab/resolve/main/"
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_AUDIO_URL = _BASE_URL + "audio/{lang}/{split}/{lang}_{split}_{shard_idx}.tar"
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_TRANSCRIPT_URL = _BASE_URL + "transcript/{lang}/{split}.
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_N_SHARDS_URL = _BASE_URL + "n_shards.json"
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@@ -102,7 +102,8 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
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)
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features = datasets.Features(
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{
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"
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"sentence": datasets.Value("string"),
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"up_votes": datasets.Value("int64"),
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"down_votes": datasets.Value("int64"),
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@@ -165,8 +166,8 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
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with open(meta_path, encoding="utf-8") as f:
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reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
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for row in tqdm(reader, desc="Reading metadata..."):
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if not row["
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row["
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# # accent -> accents in CV 8.0
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# if "accents" in row:
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# row["accent"] = row["accents"]
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@@ -175,7 +176,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
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for field in data_fields:
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if field not in row:
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row[field] = ""
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metadata[row["
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for i, audio_archive in enumerate(archives):
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for path, file in audio_archive:
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@@ -184,6 +185,6 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
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result = dict(metadata[filename])
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# set the audio feature and the path to the extracted file
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path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
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result["audio
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result["
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yield path, result
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_CITATION = """\
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+
@inproceedings{TericLabs:2023,
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author = {Bateesa, T. and Wairagala, EP. },
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title = {Teric Lab: A Massively-Multilingual Speech Corpus},
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}
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_AUDIO_URL = _BASE_URL + "audio/{lang}/{split}/{lang}_{split}_{shard_idx}.tar"
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_TRANSCRIPT_URL = _BASE_URL + "transcript/{lang}/{split}.tsv"
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_N_SHARDS_URL = _BASE_URL + "n_shards.json"
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)
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features = datasets.Features(
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{
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"path": datasets.Value("string"),
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"audio": datasets.features.Audio(sampling_rate=48_000),
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"sentence": datasets.Value("string"),
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"up_votes": datasets.Value("int64"),
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"down_votes": datasets.Value("int64"),
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with open(meta_path, encoding="utf-8") as f:
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reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
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for row in tqdm(reader, desc="Reading metadata..."):
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if not row["path"].endswith(".wav"):
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row["path"] += ".wav"
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# # accent -> accents in CV 8.0
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# if "accents" in row:
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# row["accent"] = row["accents"]
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for field in data_fields:
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if field not in row:
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row[field] = ""
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metadata[row["path"]] = row
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for i, audio_archive in enumerate(archives):
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for path, file in audio_archive:
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result = dict(metadata[filename])
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# set the audio feature and the path to the extracted file
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path = os.path.join(local_extracted_archive_paths[i], path) if local_extracted_archive_paths else path
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result["audio"] = {"path": path, "bytes": file.read()}
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result["path"] = path
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yield path, result
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