Discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition

In this paper we propose discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition tasks. After presenting our hierarchical modeling framework, we describe how the models can be generated with either Minimum Classification Error or large-margin training. Experiments on a large vocabulary lecture transcription task show that the hierarchical model can yield more than

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Hung-An Chang, James R. Glass
• Keywords: Hierarchical Acoustic Models, Hierarchical Modeling Framework, ICASSP 2009, Large Vocabulary, Signal Processing