Decode a 16-bit PCM WAV file to a float tensor.
tf.audio.decode_wav(
contents: _atypes.TensorFuzzingAnnotation[_atypes.String],
desired_channels: int = -1,
desired_samples: int = -1,
name=None
)
The -32768 to 32767 signed 16-bit values will be scaled to -1.0 to 1.0 in float.
When desired_channels is set, if the input contains fewer channels than this then the last channel will be duplicated to give the requested number, else if the input has more channels than requested then the additional channels will be ignored.
If desired_samples is set, then the audio will be cropped or padded with zeroes to the requested length.
The first output contains a Tensor with the content of the audio samples. The lowest dimension will be the number of channels, and the second will be the number of samples. For example, a ten-sample-long stereo WAV file should give an output shape of [10, 2].
Returns | |
---|---|
A tuple of Tensor objects (audio, sample_rate).
|
|
audio
|
A Tensor of type float32 .
|
sample_rate
|
A Tensor of type int32 .
|