Using syllables as acoustic units for spontaneous speech recognition

Abstract

In this work, we deal with advanced context-dependent automatic speech recognition (ASR) of Czech spontaneous talk using hidden Markov models (HMM). Context-dependent units (e.g. triphones, diphones) in ASR systems provide significant improvement against simple non-context-dependent units. However, for spontaneous speech recognition we had to overcome some very challenging tasks. For one, the number of syllables compared to the size of spontaneous speech corpus makes the usage of context-dependent units very difficult. The main part of this article shows problems and procedures to effectively build and use a syllable-based ASR with the LASER (ASR system developed at Department of Computer Science and Engineering, Faculty of Applied Sciences). The procedures are usable with virtual any modern ASR. © 2010 Springer-Verlag Berlin Heidelberg.