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) discriminative training framework, while the second stage performs linear discrimination combining the output of the first stage with HMM likelihood scores. In this fashion the classification power of the HMM is combined with that of the GPD stage which is specifically designed for keyword/nonkeyword classification. Experimental
This paper presents a system for speaker independent keyword spotting (KWS) in continuous speech using a spoken example template. The approach, based on Dynamic Time Warping (DTW) for matching the template to a test utterance, does not require any modelling or training as required in alternative techniques such as the
accurately locate the occurrences of a list of keywords in a broadcast corpus. Textual information from the transcripts and an efficient rescoring scheme are used to improve the performance of the phonetic search. Our experiments show that the proposed method outperforms the baseline textual and phonetic searches by its ability
This work compares ASR decoding at different subword levels crossed with alternative keyword search strategies to handle the OOV issue for keyword spotting in the low-resource setting. We show that a morpheme-based subword modeling approach is effective in recovering OOV keywords within a Turkish low-resource keyword
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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