Biometric Voice Identification Based on Fuzzy Kernel Classifier

2014 International Conference on Multimedia Computing and Systems (ICMCS)

Izydorczyk

2014

Self Cite

This paper presents speaker recognition system possessing very good generalization properties. Relatively low equal error rate for speaker verification and high identification rate for identification are achieved for very short training and testing sequences. This behaviour is achieved for the kernel modification of a classic Ho-Kashyap linear classifier. Achieved results for the new approach are compared with results for the classic GMM and VQ techniques. Speech of a moderately good quality from the Polish speech corpus was used for development of recognition system.

Section: Introductionmentioning

confidence: 99%

Speaker recognition system with good generalization properties

Dustor

2014 International Conference on Multimedia Computing and Systems (ICMCS)

Izydorczyk

2014

Self Cite

“…The main goal of research on the conversion of graphemes to phonemes is improving speech recognition for the Polish language [5,6]. In addition, research studies have been conducted on the phonetic properties of Polish phonemes [7,8], speech recognition based on such analyses [9], speaker recognition [10][11][12][13][14] and new applications of speech and language processing (e.g., speech translation) [15]. Particularly good results in speech recognition are achieved through the use of statistical language models [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Rule-Based Grapheme-to-Phoneme Conversion System

2022

Applied Sciences

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This article presents a rule-based grapheme-to-phoneme conversion method and algorithm for Polish. It should be noted that the fundamental grapheme-to-phoneme conversion rules have been developed by Maria Steffen-Batóg and presented in her set of monographs dedicated to the automatic grapheme-to-phoneme conversion of texts in Polish. The author used previously developed rules and independently developed the grapheme-to-phoneme conversion algorithm.The algorithm has been implemented as a software application called TransFon, which allows the user to convert any text in Polish orthography to corresponding strings of phonemes, in phonemic transcription. Using TransFon, a phonemic Polish language corpus was created out of an orthographic corpus. The phonemic language corpusallows statistical analysis of the Polish language, as well as the development of phoneme- and word-based language models for automatic speech recognition using statistical methods. The developed phonemic language corpus opens up further opportunities for research to improve automatic speech recognition in Polish. The development of statistical methods for speech recognition and language modelling requires access to large language corpora, including phonemic corpora. The method presented here enables the creation of such corpora.

“…Additionally, Correspondence: pklosowski@polsl.pl Department of Electronics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland research studies have been conducted in the field of properties of Polish phonemes [8,9], speech recognition based on it [10], speaker recognition [11,12], speaker verification [13][14][15], and new applications of speech recognition, e.g., automatic speech translation [16].…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis of orthographic and phonemic language corpus for word-based and phoneme-based Polish language modelling

J AUDIO SPEECH MUSIC PROC.

2017

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This article presents the original results of Polish language statistical analysis, based on the orthographic and phonemic language corpus. Phonemic language corpus for Polish was developed by using automatic grapheme-to-phoneme conversion of the source orthographic language corpus, obtained from the National Corpus of Polish (NCP). The corpus contains the most frequently used Polish words, written with the use of phonemic notation. Performed statistical analysis of Polish language based on phonemic language corpus, includes frequency of occurrence calculation of the orthographic and phonemic language components, as well as their sequence. Statistical language data, obtained as a result of performed statistical analysis, enable to develop statistical word-based and phoneme-based language models for Polish. Applying these language models can effectively contribute to efficiency improvement of automatic speech recognition for Polish.