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spontaneous speech with momentous word error rate, which is a negative aspect of standard retrieval system. To prevail over such a constraint, we propose a method for spoken document retrieval based on spoken keyword spotting using Auto Associative Neural Networks (AANN). The proposed work concerns the exploit of the
The paper presents unsupervised method for word detection in recorded spoken language signal. The method is based on examining signal similarity of two analyzed media description: registered voice and a word (textual query) synthesized by using Text-to-Speech tools. The descriptions of media were given by a sequence of Mel-Frequency Cepstral Coefficients or Human-Factor Cepstral Coefficients. Dynamic...
(ANN) based hybrid phoneme recognizer. The phone posteriors of query word and reference data are matched by using the non-segmental Dynamic Time Warping (DTW) technique. In order to make the decision about the presence or absence of a keyword in a particular reference file, image processing based approach is proposed. The
In this paper, the effect of keyword choice including and excluding plosive sounds on isolated speaker recognition system is investigated. In order to perform this study, a Turkish word database has been created consisting of 48 words including plosives and 7 words without plosives. Records are acquired at a sampling
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