Third European Conference on Speech Communication and Technology

Berlin, Germany
September 22-25, 1993


Word Spotting in Conversational Speech Based on Phonemic Unit Likelihood by Mutual Information Criterion

Shigeki Okawa, Tetsunori Kobayashi, Katsuhiko Shirai

Department of Electrical Engineering, WASEDA University, Tokyo, Japan

This paper proposes a novel scheme for keyword-spotting in conversational speech using frame-level likelihood of phonemes and statistics of their duration. Since spontaneous utterances include many ill-formed sentences, it is most difficult to realize a highly advanced continuous speech recognition system based on a top-down syntax driven process. We, therefore, propose a bottom-up method to detect keywords in continuous speech based on a dynamical programming technique using both phonemic and durational likelihood. Our algorithm basically depends on island-driven both-side-free DP method. In the performance test of the speaker-dependent keyword spotting, it was found that, compared to the conventional continuous DP method, the erroneous candidates and the processing time decreases to 1/6 in new method. This result shows the feasibility of our method for continuous speech recognition, especially for conversational style utterances.

Full Paper

Bibliographic reference.  Okawa, Shigeki / Kobayashi, Tetsunori / Shirai, Katsuhiko (1993): "Word spotting in conversational speech based on phonemic unit likelihood by mutual information criterion", In EUROSPEECH'93, 1281-1284.