Decodes the output of a softmax.

Can use either greedy search (also known as best path) or a constrained dictionary search.

k_ctc_decode(y_pred, input_length, greedy = TRUE, beam_width = 100L,
  top_paths = 1)

Arguments

y_pred	tensor `(samples, time_steps, num_categories)` containing the prediction, or output of the softmax.
input_length	tensor `(samples, )` containing the sequence length for each batch item in `y_pred`.
greedy	perform much faster best-path search if `TRUE`. This does not use a dictionary.
beam_width	if `greedy` is `FALSE`: a beam search decoder will be used with a beam of this width.
top_paths	if `greedy` is `FALSE`, how many of the most probable paths will be returned.

Value

If greedy is TRUE, returns a list of one element that contains the decoded sequence. If FALSE, returns the top_paths most probable decoded sequences. Important: blank labels are returned as -1. Tensor (top_paths) that contains the log probability of each decoded sequence.

Keras Backend

This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).

You can see a list of all available backend functions here: https://keras.rstudio.com/articles/backend.html#backend-functions.