Phonetic recognition for spoken document retrieval

This paper describes the development and application of a phonetic recognition system to the task of spoken document retrieval. The recognizer is used to generate phonetic transcriptions of the speech messages which are then processed to produce subword unit representations for indexing and retrieval. Subword units are used as an alternative to words units generated by either keyword spotting or word recognition. We first investigate the use of different acoustic and language models in the speech recognizer in an effort to improve phonetic recognition performance. Then we examine a variety of subword unit indexing terms and measure their ability to perform effective spoken document retrieval. Finally, we look at some simple robust indexing and retrieval methods that take into account the characteristics of the recognition errors in an attempt to improve retrieval performance