Updated README.md
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README.md
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@@ -104,18 +104,18 @@ Train your own CTC or Seq2Seq Automatic Speech Recognition models on Nigerian Ac
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### Data Instances
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A typical data point comprises the `path` to the audio file and its `sentence`.
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Additional fields include `accent`, `
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```python
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{
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'client_id': 'user_3279',
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'path': 'clips/audio_sample_3280.mp3',
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'audio':
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'
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'accent': 'nigerian',
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'locale': 'en',
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'segment': None
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`path` (`string`): The path to the audio file
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`audio` (`string`):
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`sentence` (`string`): The sentence the user was prompted to speak
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`up_votes` (`int64`): How many upvotes the audio file has received from reviewers
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`down_votes` (`int64`): How many downvotes the audio file has received from reviewers
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`age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`)
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`gender` (`string`): The gender of the speaker
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`accent` (`string`): Accent of the speaker
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`locale` (`string`): The locale of the speaker
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### Data Instances
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A typical data point comprises the `path` to the audio file and its `sentence`.
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Additional fields include `accent`, `client_id`, `locale` and `segment`.
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```python
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{
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'client_id': 'user_3279',
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'path': 'clips/audio_sample_3280.mp3',
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'audio': {
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'path': 'clips/audio_sample_1.mp3',
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'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32),
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'sampling_rate': 48000
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},
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'sentence': 'Its images were used by among others Palestinians in their protest against Israel',
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'accent': 'nigerian',
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'locale': 'en',
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'segment': None
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`path` (`string`): The path to the audio file
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`audio` (`string`): audio (dict): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate.
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Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate.
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Decoding and resampling of a large number of audio files might take a significant amount of time.
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Thus it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0]
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`sentence` (`string`): The sentence the user was prompted to speak
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`accent` (`string`): Accent of the speaker
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`locale` (`string`): The locale of the speaker
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