16th Annual Conference of the International Speech Communication Association

Dresden, Germany
September 6-10, 2015

Ant Colony Algorithm Applied to Automatic Speech Recognition Graph Decoding

Benjamin Lecouteux, Didier Schwab

LIG (UMR 5217), France

In this article we propose an original approach that allows the decoding of Automatic Speech Recognition Graphs by using a constructive algorithm based on ant colonies. In classical approaches, when a graph is decoded with higher order language models; the algorithm must expand the graph in order to develop each new observed n-gram. This extension process increases the computation time and memory consumption. We propose to use an ant colony algorithm in order to explore ASR graphs with a new language model, without the necessity of expanding it. We first present results based on the TED English corpus where 2-grams graph are decoded with a 4-grams language model. Then, we show that our approach performs better than a conventional Viterbi algorithm when computing time is constrained and allows a highly threaded decoding process with a single graph and a strict control of computation time and memory consumption.

Full Paper

Bibliographic reference.  Lecouteux, Benjamin / Schwab, Didier (2015): "Ant colony algorithm applied to automatic speech recognition graph decoding", In INTERSPEECH-2015, 2122-2126.