CTCGreedyDecoder

Versioned name: CTCGreedyDecoder-1

Category: Sequence processing

Short description: CTCGreedyDecoder performs greedy decoding on the logits given in input (best path).

Detailed description:

This operation is similar Reference

Given an input sequence \(X\) of length \(T\), CTCGreedyDecoder assumes the probability of a length \(T\) character sequence \(C\) is given by

\[ p(C|X) = \prod_{t=1}^{T} p(c_{t}|X) \]

Sequences in the batch can have different length. The lengths of sequences are coded as values 1 and 0 in the second input tensor sequence_mask. Value sequence_mask[j, i] specifies whether there is a sequence symbol at index i in the sequence i in the batch of sequences. If there is no symbol at j-th position sequence_mask[j, i] = 0, and sequence_mask[j, i] = 1 otherwise. Starting from j = 0, sequence_mass[j, i] are equal to 1 up to the particular index j = last_sequence_symbol, which is defined independently for each sequence i. For j > last_sequence_symbol, values in sequence_mask[j, i] are all zeros.

Note: Regardless of the value of ctc_merge_repeated attribute, if the output index for a given batch and time step corresponds to the blank_index, no new element is emitted.

Attributes

  • ctc_merge_repeated
    • Description: ctc_merge_repeated is a flag for merging repeated labels during the CTC calculation.
    • Range of values: true or false
    • Type: boolean
    • Default value: true
    • Required: no

Inputs

  • 1: data - Input tensor with a batch of sequences. Type of elements is any supported floating point type. Shape of the tensor is [T, N, C], where T is the maximum sequence length, N is the batch size and C is the number of classes. Required.
  • 2: sequence_mask - 2D input floating point tensor with sequence masks for each sequence in the batch. Populated with values 0 and 1. Shape of this input is [T, N]. Required.

Output

  • 1: Output tensor with shape [N, T, 1, 1] and integer elements containing final sequence class indices. A final sequence can be shorter that the size T of the tensor, all elements that do not code sequence classes are filled with -1. Type of elements is floating point, but all values are integers.

Example

<layer ... type="CTCGreedyDecoder" ...>
<data ctc_merge_repeated="true" />
<input>
<port id="0">
<dim>20</dim>
<dim>8</dim>
<dim>128</dim>
</port>
<port id="1">
<dim>20</dim>
<dim>8</dim>
</port>
</input>
<output>
<port id="0">
<dim>8</dim>
<dim>20</dim>
<dim>1</dim>
<dim>1</dim>
</port>
</output>
</layer>