Sixth International Conference on Spoken Language Processing
This paper presents our automatic speech recognition engine ESPERE and several results obtained from experiments on telephone speech. ESPERE (Engine for SPEech REcognition) is a HMMbased toolbox for speech recognition allowing the user to choose the modeled unit (word, phone, triphone), define the topology of every Hidden Markov Model, train the models with the Baum-Welch algorithm and evaluate the recognition accuracy on speech databases. To validate the ESPERE toolbox, we have conducted tests on real world data: the recognition of a three-digit code to access a call center. We have investigated the influence of some parameters and some preprocessing algorithms. Finally, combining the best parameters, the recognition score reaches 96.4% at the word level and 92.1% at the sentence level.
Bibliographic reference. Fohr, Dominique / Mella, Odile / Antoine, Christophe (2000): "The automatic speech recognition engine ESPERE: experiments on telephone speech", In ICSLP-2000, vol.4, 246-249.