Datasets:
Commit
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dc01e20
1
Parent(s):
ed16922
Add word/phone level scores
Browse files- README.md +22 -5
- speechocean762.py +14 -0
README.md
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@@ -42,10 +42,10 @@ pip install soundfile
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>>> next(iter(test_set))
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{'file': 'WAVE/SPEAKER0003/000030012.WAV',
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'audio': {
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'text': 'MARK IS GOING TO SEE ELEPHANT',
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'speaker': '0003',
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'gender': 'm',
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@@ -53,7 +53,24 @@ pip install soundfile
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'accuracy': 9,
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'fluency': 9,
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'prosodic': 9,
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'total': 9
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```
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## The scoring metric
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>>> next(iter(test_set))
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{'file': 'WAVE/SPEAKER0003/000030012.WAV',
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'audio': {
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'path': 'WAVE/SPEAKER0003/000030012.WAV',
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'array': array([-0.00119019, -0.00500488, -0.00283813, ..., 0.00274658, 0. , 0.00125122]),
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'sampling_rate': 16000},
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'text': 'MARK IS GOING TO SEE ELEPHANT',
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'speaker': '0003',
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'gender': 'm',
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'accuracy': 9,
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'fluency': 9,
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'prosodic': 9,
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'total': 9,
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'words': {'text': ['MARK', 'IS', 'GOING', 'TO', 'SEE', 'ELEPHANT'],
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'accuracy': [10, 10, 10, 10, 10, 10],
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'stress': [10, 10, 10, 10, 10, 10],
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'total': [10, 10, 10, 10, 10, 10],
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'phones': [['M', 'AA0', 'R', 'K'],
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['IH0', 'Z'],
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['G', 'OW0', 'IH0', 'NG'],
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['T', 'UW0'],
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['S', 'IY0'],
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['EH1', 'L', 'IH0', 'F', 'AH0', 'N', 'T']],
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'phones-accuracy': [[2.0, 2.0, 1.8, 2.0],
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[2.0, 1.8],
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[2.0, 2.0, 2.0, 2.0],
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[2.0, 2.0],
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[2.0, 2.0],
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[2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0]],
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'mispronunciations': ['[]', '[]', '[]', '[]', '[]', '[]']}}
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```
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## The scoring metric
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speechocean762.py
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@@ -71,6 +71,19 @@ class Speechocean762(datasets.GeneratorBasedBuilder):
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"fluency": datasets.Value("int16"),
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"prosodic": datasets.Value("int16"),
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"total": datasets.Value("int16"),
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}
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),
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homepage=_HOMEPAGE,
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@@ -110,4 +123,5 @@ class Speechocean762(datasets.GeneratorBasedBuilder):
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"fluency": row["fluency"],
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"prosodic": row["prosodic"],
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"total": row["total"],
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}
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"fluency": datasets.Value("int16"),
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"prosodic": datasets.Value("int16"),
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"total": datasets.Value("int16"),
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"words": datasets.Sequence(
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feature={
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"text": datasets.Value("string"),
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"accuracy": datasets.Value("int16"),
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"stress": datasets.Value("int16"),
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"total": datasets.Value("int16"),
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"phones": datasets.Sequence(datasets.Value("string")),
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"phones-accuracy": datasets.Sequence(
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datasets.Value("float")
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),
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"mispronunciations": datasets.Value("string"),
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}
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),
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}
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),
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homepage=_HOMEPAGE,
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"fluency": row["fluency"],
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"prosodic": row["prosodic"],
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"total": row["total"],
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"words": row["words"],
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}
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