Wszystkie pola: phoneme segmentation - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Phoneme Segmentation Based on Wavelet Spectra Analysis
Autorzy:: Ziółko, B.
Manandhar, S.
Wilson, R. C.
Ziółko, M.
Powiązania:: https://bibliotekanauki.pl/articles/177480.pdf
Data publikacji:: 2011
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: speech recognition
speech segmentation
discrete wavelet transform
Opis:: A phoneme segmentation method based on the analysis of discrete wavelet transform spectra is described. The localization of phoneme boundaries is particularly useful in speech recognition. It enables one to use more accurate acoustic models since the length of phonemes provide more information for parametrization. Our method relies on the values of power envelopes and their first derivatives for six frequency subbands. Specific scenarios that are typical for phoneme boundaries are searched for. Discrete times with such events are noted and graded using a distribution-like event function, which represent the change of the energy distribution in the frequency domain. The exact definition of this method is described in the paper. The final decision on localization of boundaries is taken by analysis of the event function. Boundaries are, therefore, extracted using information from all subbands. The method was developed on a small set of Polish hand segmented words and tested on another large corpus containing 16 425 utterances. A recall and precision measure specifically designed to measure the quality of speech segmentation was adapted by using fuzzy sets. From this, results with F-score equal to 72.49% were obtained.
Źródło:: Archives of Acoustics; 2011, 36, 1; 29-47
0137-5075
Pojawia się w:: Archives of Acoustics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Unsupervised Phoneme Segmentation Based on Main Energy Change for Arabic Speech
Autorzy:: Lachachi, N.
Powiązania:: https://bibliotekanauki.pl/articles/958116.pdf
Data publikacji:: 2017
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: band frequencies
energy changes
formant analysis
phoneme segmentation
Opis:: In this paper, a new method for segmenting speech at the phoneme level is presented. For this purpose, author uses the short-time Fourier transform of the speech signal. The goal is to identify the locations of main energy changes in frequency over time, which can be described as phoneme boundaries. A frequency range analysis and search for energy changes in individual area is applied to obtain further precision to identify speech segments that carry out vowel and consonant segment confined in small number of narrow spectral areas. This method merely utilizes the power spectrum of the signal for segmentation. There is no need for any adaptation of the parameters or training for different speakers in advance. In addition, no transcript information, neither any prior linguistic knowledge about the phonemes is needed, or voiced/unvoiced decision making is required. Segmentation results with proposed method have been compared with a manual segmentation, and compared with three same kinds of segmentation methods. These results show that 81% of the boundaries are successfully identified. This research aims to improve the acoustic parameters for all the processing systems of the Arab speech.
Źródło:: Journal of Telecommunications and Information Technology; 2017, 1; 12-20
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Speech Segmentation Algorithm Based on an Analysis of the Normalized Power Spectral Density
Autorzy:: Pekar, D.
Tsikhanenka, S.
Powiązania:: https://bibliotekanauki.pl/articles/308533.pdf
Data publikacji:: 2010
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: phoneme segmentation
power spectral density
short-term signal energy
speaker independent
voice systems
Opis:: This article demonstrates a new approach to speaker independent phoneme detection. The core of the algorithm is to measure the distance between normalized power spectral densities in adjacent, short-time segments and verify it based on velocity of changes of values of short-time signal energy analysis. The results of experiment analysis indicate that proposed algorithm allows revealing a phoneme structure of pronounced speech with high probability. The advantages of this algorithm are absence of any prior information on a signal or model of phonemes and speakers that allows the algorithm to be speaker independent and have a low computation complexity.
Źródło:: Journal of Telecommunications and Information Technology; 2010, 4; 44-49
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Automatic speech signal segmentation based on the innovation adaptive filter
Autorzy:: Makowski, R.
Hossa, R.
Powiązania:: https://bibliotekanauki.pl/articles/330096.pdf
Data publikacji:: 2014
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: automatic speech segmentation
inter phoneme boundaries
Schur adaptive filtering
detection threshold determination
automatyczna segmentacja mowy
filtracja adaptacyjna
określenie progu detekcji
Opis:: Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006), and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 259-270
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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