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Combining Confusion Networks with probabilistic phone matching for open-vocabulary keyword spotting in spontaneous speech signal
Citation key 1214Jin2009
Author Shan Jin and Thomas Sikora
Title of Book 17th in a series of conferences organised by the European Association for Signal, Speech, and Image Processing (EUSIPCO 2009)
Year 2009
Address Glasgow, Scotland
Month aug
Organization The European Association for Signal Processing (EURASIP)
Abstract In this paper, we study several methods for keyword spotting in spontaneous speech signal. Novel method combining probabilistic phone matching (PSM) approach with word confusion networks (WCN) is proposed for open-vocabulary keyword spotting task. This method runs keyword spotting on multi-level transcriptions (WCN and phone-onebest). We propose to use classical string matching for word spotting on WCN. At the same time probabilistic string matching is used for acoustic word spotting on phone-onebest transcription. It is verified that the novel hybrid method outperforms WCN-based and PSM-based approaches in-vocabulary and out-of-vocabulary (OOV) keywords.
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