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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 develop a new approach to ECG analysis, combining Pitch Synchronous Wavelet Transform (PSWT) and Hidden Semi-Markov Model (HSMM) for tracking the typical ECG cycle. The combination of these two techniques was examined in a way that the PSWT of an ECG signal was an input for the HSMM. This approach was tested and evaluated on the manually annotated QT database. Experimental results...
In this paper, a feature extraction method for robust speech recognition in noisy environments is proposed. The proposed method is motivated by a biologically inspired auditory model which simulates the outer/middle ear filtering by a low-pass filter and the spectral behaviour of the cochlea by the Gammachirp auditory filterbank (GcFB). The speech recognition performance of our method is tested on...
This paper describes a recognition system based on diverse features combination for the automatic heartbeat recognition purpose. The method consists of three stages: at the first stage, we extract a set of features including the morphological ones, high order statistics and pitch synchronous decomposition from ECG data using QT database; at the second stage, we use the hidden Markov tree classifier,...
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