CTCModel: a Keras Model for Connectionist Temporal Classification

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. wit...

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Bibliographic Details
Published in:arXiv.org 2019-01
Main Authors: Soullard, Yann, Ruffino, Cyprien, Paquet, Thierry
Format: Article
Language:English
Subjects:
Classification
Labels
Mathematical models
Predictions
Recurrent neural networks
Sequences
Training
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Summary: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.
ISSN:2331-8422