DESCRIPTION OF ACOUSTIC VARIATIONS BY TREE-BASED PHONE MODELING

This paper discusses the use of tree-based phone modeling to describe acoustic variations of speech, and its application to speech recognition system. There are many sources of variabilities that affect the realization of a phoneme: phonetic contexts, speakers, stress, speaking rates and so on. Explicit modeling with these sources of variabilities will give more accurate and more detailed phone models, but needs a large amount of speech data for training. Tree-based phone modeling is studied to solve this problem with three case studies: phone models with large VQ codebook sizes, decision tree clustering, and speaker-clustering. They are tested on speakerindependent continuous speech recognition experiments with a 991 word vocabulary. Tree-based phone modeling is shown to produce improvement in all three cases and to provide a good guide to provide trainability and generalizability.