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This paper presents a novel architecture for keyword spotting in spontaneous speech, in which keyword model is trained from a small number of acoustic examples provided by a user. The word-spotting architecture relies on scoring patch feature vector sequences extracted by using sliding windows, and performing keyword
This paper proposes a multistage utterance verification method as a post-processing technique for online spoken content retrieval in portable electric devices. The online spoken content retrieval system analyzes spoken content in an online manner and searches speech segments of pre-defined keywords. To maintain stable
actual language identification. On our bi-lingual lecture tasks the PPRLM system clearly outperforms the PPR system in various segment length conditions, however at the cost of slower run-time. By using lexical information in the form of keyword spotting, and additional language models we show ways to improve the
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