| Paper: | SLP-P15.3 | ||
| Session: | Spoken Document Search, Navigation and Summarization | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech and Spoken Language Processing: Speech data mining and document retrieval | ||
| Title: | KEYWORD SPOTTING OF ARBITRARY WORDS USING MINIMAL SPEECH RESOURCES | ||
| Authors: | Alvin Garcia, Herbert Gish, BBN Technologies, United States | ||
| Abstract: | Traditional approaches to keyword spotting employ a large vocabulary speech recognizer, phone recognizer or a whole-word approach such as whole-word Hidden Markov Models. In any of these approaches, considerable speech resources are required to create a word spotting system. In this paper we describe a keyword spotting system that requires about fifteen minutes of word-level transcriptions of speech as its sole annotated resource. The system uses our self-organizing speech recognizer that defines its own sound units as a recognizer for the speech in the speech domain under consideration. The transcriptions are used to train a grapheme-to-sound-unit converter. We describe this novel system and give its keyword spotting performance. | ||
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