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This paper presents an improved acoustic keyword spotting (KWS) algorithm using a novel confusion garbage model in Mandarin conversational speech. Observing the KWS corpus, we found there are many words with similar pronunciation with predefined keywords, although they have different Chinese characters and different
of vocabulary words in the users speech utterance. In this paper, we investigate an approach that can be deployed in keyword spotting systems. We propose a phoneme classifier that will be ultimately used to provide confidence values to be compared against existing Automatic Speech Recognizer word confidences. The end
prototype system demonstrates our latest development on automatic speech recognition, keyword spotting, personalized text-to-speech synthesis and visual speech synthesis. The second demo exhibits a virtual concert with immersive audio effects. Through our virtual auditory technology, wearing simple earphones, listeners are
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