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torchaudio.functional.forced_align

torchaudio.functional.forced_align(log_probs: Tensor, targets: Tensor, input_lengths: Optional[Tensor] = None, target_lengths: Optional[Tensor] = None, blank: int = 0) Tuple[Tensor, Tensor][source]

Align a CTC label sequence to an emission.

This feature supports the following devices: CPU, CUDA This API supports the following properties: TorchScript
Parameters:
  • log_probs (Tensor) – log probability of CTC emission output. Tensor of shape (B, T, C). where B is the batch size, T is the input length, C is the number of characters in alphabet including blank.

  • targets (Tensor) – Target sequence. Tensor of shape (B, L), where L is the target length.

  • input_lengths (Tensor or None, optional) – Lengths of the inputs (max value must each be <= T). 1-D Tensor of shape (B,).

  • target_lengths (Tensor or None, optional) – Lengths of the targets. 1-D Tensor of shape (B,).

  • blank_id (int, optional) – The index of blank symbol in CTC emission. (Default: 0)

Returns:

Tensor: Label for each time step in the alignment path computed using forced alignment.

Tensor: Log probability scores of the labels for each time step.

Return type:

Tuple(Tensor, Tensor)

Note

The sequence length of log_probs must satisfy:

\[L_{\text{log\_probs}} \ge L_{\text{label}} + N_{\text{repeat}} \]

where \(N_{\text{repeat}}\) is the number of consecutively repeated tokens. For example, in str “aabbc”, the number of repeats are 2.

Note

The current version only supports batch_size==1.

Tutorials using forced_align:
CTC forced alignment API tutorial

CTC forced alignment API tutorial

CTC forced alignment API tutorial
Forced alignment for multilingual data

Forced alignment for multilingual data

Forced alignment for multilingual data
Forced Alignment with Wav2Vec2

Forced Alignment with Wav2Vec2

Forced Alignment with Wav2Vec2

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