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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...
Despite the advances of information technology tools in the speech recognition task, the challenge to find a rapid and an efficient approach remains a principal research topic. In this paper, we apply the k-nearest neighbors (kNN) algorithm for Timit phoneme recognition with two models: crisp and fuzzy. Essentially, we explore the contribution of the fuzzy aspect for the crisp version of the kNN algorithm...
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 will present an educational software designed for signal and speech processing applications. This interface which was developed under Matlab, can be used for signal denoising, speech coding and recognition. The implemented algorithms take into account the G723-G729 UIT specifications. The main menu was divided into six under-menus devoted for signal waveform representation, signal...
In this work, we study speech analysis techniques to classify phoneme using a method of fuzzy logic. The used techniques are Mel Frequency Cepstral Coefficient (MFCC), Perceptual Linear Prediction (PLP) and RelAtive SpecTrAl-Perceptual Linear Prediction (RASTA-PLP). The fuzzy logic method is characterized by three fuzzy reference vectors: the maximal vector, the mean vector and the minimal vector...
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