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In this work, the Fuzzy kNN (FkNN), an alternative of the standard kNN algorithm, is used for Timit phoneme recognition. Phoneme is the smallest unit that composes speech. For this reason, if phoneme recognition is performed, it can achieve a significant word and text recognition. Thus, the main idea consists on assigning phoneme membership to the data phonemes by measuring the distance to its kNN...
In this paper we describe a systematic procedure to implement two-stage based keywords spotting system (KWS). In first stage, a phonetic decoding of continuous speech is obtained using a CD-DNN-HMM model built with the Kaldi toolkit. In second stage, these results of phonetic transcriptions will serve to construct a system to search the keywords embedded in continuous speech using the classification...
In this work, the Fuzzy kNN (FkNN), an alternative of the standard kNN algorithm, is used for Timit phoneme recognition. Phoneme is the smallest unit that composes speech. For this reason, if phoneme recognition is performed, it can achieve a significant word and text recognition. Thus, the main idea consists on assigning phoneme membership to the data phonemes by measuring the distance to its kNN...
We report on a comparison of fuzzy and HMM phoneme recognizers of data Timit corpus. We aimed to check an optimal number of signal cepstral coefficients for both a1pproaches. For this purpose, we used different parameterization techniques such as MFCC, LPCC and PLP. Also, coefficient numbers has been varied from 12 to 39 including first and second derivatives and signal energy to introduce signal...
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