athena.data.datasets.vad.vad_set_kaldiio

audio dataset

Module Contents

Classes

VoiceActivityDetectionDatasetKaldiIOBuilder

VoiceActivityDetectionDatasetKaldiIOBuilder

class athena.data.datasets.vad.vad_set_kaldiio.VoiceActivityDetectionDatasetKaldiIOBuilder(config=None)

Bases: athena.data.datasets.base.SpeechBaseDatasetBuilder

VoiceActivityDetectionDatasetKaldiIOBuilder

property sample_type

@property

Returns

sample_type of the dataset:

{
    "input": tf.float32,
    "input_length": tf.int32,
    "output_length": tf.int32,
    "output": tf.int32,
}

Return type

dict

property sample_shape

@property

Returns

sample_shape of the dataset:

{
    "input": tf.TensorShape([None, dim, nc]),
    "input_length": tf.TensorShape([]),
    "output_length": tf.TensorShape([]),
    "output": tf.TensorShape([None]),
    "utt": tf.TensorShape([]),
}

Return type

dict

property sample_signature

@property

Returns

sample_signature of the dataset:

{
    "input": tf.TensorSpec(shape=(None, None, dim, nc), dtype=tf.float32),
    "input_length": tf.TensorSpec(shape=(None), dtype=tf.int32),
    "output_length": tf.TensorSpec(shape=(None), dtype=tf.int32),
    "output": tf.TensorSpec(shape=(None, None), dtype=tf.int32),
    utt": tf.TensorSpec(shape=(None), dtype=tf.string),
}

Return type

dict

default_config

preprocess_data(data_scps_dir)

generate a list of tuples (wav_filename, wav_offset, wav_length_ms, transcript, label).

splice_feature(feature)

splice features according to input_left_context and input_right_context input_left_context: the left features to be spliced,

repeat the first frame in case out the range

input_right_context: the right features to be spliced,

repeat the last frame in case out the range

Parameters

feature – the input features, shape may be [timestamp, dim, 1]

Returns

the spliced features

Return type

splice_feat

__getitem__(index)

get a sample

Parameters

index (int) – index of the entries

Returns

sample:

{
    "input": feat,
    "input_length": feat_length,
    "output_length": label_length,
    "output": label,
    "utt": utt
}

Return type

dict