Third International Conference on Spoken Language Processing (ICSLP 94)
In this paper, we describe a real-time keyword-spotting unit (KeySpot) with an adaptive noise-canceller for speaker-independent, spontaneous speech recognition in noisy environments. KeySpot consists of a DSP (TMS320C30) for adaptive noise-cancellation and acoustic analysis, a special LSI for statistical matrix quantization (SMQ), two SPARC chips ('SPARC1' and 'SPARC2') for HMM based keyword-spotting, and a SPARC chip ('SPARC3') for syntactic analysis. KeySpot was tested under two conditions: a speaker-independent large-vocabulary isolated word recognizer, and a speaker-independent small-vocabulary word spotter. Evaluation results have shown that KeySpot can be used for the speaker-independent, 1000 isolated word recognizer with an accuracy of 96.3%, as well as the 90 word vocabulary word spotter with an accuracy of 94.4% with a response time of 0.3 sec.
Bibliographic reference. Masai, Yasuyuki / Iwasaki, Jun'Ichi / Tanaka, Shin'Ichi / Nitta, Tsuneo / Yao, Masahiro / Onogi, Tomohiro / Nakayama, Akira (1994): "A keyword-spotting unit for speaker-independent spontaneous speech recognition", In ICSLP-1994, 1383-1386.