Datasets:
Languages:
English
ArXiv:
Tags:
query-by-example-spoken-term-detection
audio-slot-filling
speaker-diarization
automatic-speaker-verification
License:
Update files from the datasets library (from 1.17.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.17.0
superb.py
CHANGED
@@ -137,7 +137,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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-
"audio": datasets.
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"text": datasets.Value("string"),
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"speaker_id": datasets.Value("int64"),
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"chapter_id": datasets.Value("int64"),
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@@ -162,7 +162,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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-
"audio": datasets.
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"label": datasets.ClassLabel(
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names=[
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"yes",
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@@ -196,7 +196,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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-
"audio": datasets.
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"speaker_id": datasets.Value("string"),
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"text": datasets.Value("string"),
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"action": datasets.ClassLabel(
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@@ -238,7 +238,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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-
"audio": datasets.
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# VoxCeleb1 contains 1251 speaker IDs in range ["id10001",..."id11251"]
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"label": datasets.ClassLabel(names=[f"id{i + 10001}" for i in range(1251)]),
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}
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@@ -261,7 +261,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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{
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"record_id": datasets.Value("string"),
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"file": datasets.Value("string"),
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-
"audio": datasets.
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"start": datasets.Value("int64"),
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"end": datasets.Value("int64"),
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"speakers": [
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@@ -289,7 +289,7 @@ class Superb(datasets.GeneratorBasedBuilder):
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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-
"audio": datasets.
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"label": datasets.ClassLabel(names=["neu", "hap", "ang", "sad"]),
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}
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),
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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"text": datasets.Value("string"),
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"speaker_id": datasets.Value("int64"),
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"chapter_id": datasets.Value("int64"),
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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"label": datasets.ClassLabel(
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names=[
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"yes",
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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"speaker_id": datasets.Value("string"),
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"text": datasets.Value("string"),
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"action": datasets.ClassLabel(
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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# VoxCeleb1 contains 1251 speaker IDs in range ["id10001",..."id11251"]
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"label": datasets.ClassLabel(names=[f"id{i + 10001}" for i in range(1251)]),
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}
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{
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"record_id": datasets.Value("string"),
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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"start": datasets.Value("int64"),
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"end": datasets.Value("int64"),
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"speakers": [
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features=datasets.Features(
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{
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"file": datasets.Value("string"),
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+
"audio": datasets.Audio(sampling_rate=16_000),
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"label": datasets.ClassLabel(names=["neu", "hap", "ang", "sad"]),
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}
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),
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