Title: CTCModel: a Keras Model for Connectionist Temporal Classification,
Abstract: We report an extension of a Keras Model, called CTCModel, to perform the
Connectionist Temporal Classification (CTC) in a transparent way. Combined with
Recurrent Neural Networks, the Connectionist Temporal Classification is the
reference method for dealing with unsegmented input sequences, i.e. with data
that are a couple of observation and label sequences where each label is
related to a subset of observation frames. CTCModel makes use of the CTC
implementation in the Tensorflow backend for training and predicting sequences
of labels using Keras. It consists of three branches made of Keras models: one
for training, computing the CTC loss function; one for predicting, providing
sequences of labels; and one for evaluating that returns standard metrics for
analyzing sequences of predictions.