Constructing telephone acoustic models from a high-quality speech corpus

In this paper we explore the effectiveness of constructing telephone acoustic models using a high-quality speech corpus. Results are presented for several front-end signal processing and feature mapping techniques. The algorithms were tested using SRI´s DECIPHER speech recognition system on several telephone corpora. The results show that (a) most of the performance loss when testing on telephone speech is due to the loss of information associated with the telephone bandwidth; (b) telephone-bandwidth systems trained with high-quality speech can outperform systems that are trained on telephone speech when tested on telephone speech; and (c) robust signal processing can allow speech recognizers to maintain performance when wide-bandwidth acoustic models are tested with telephone speech