Autor: Smolka, I. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Automatic prolongation recognition in disordered speech using CWT and Kohonen network
Autorzy:: Codello, I.
Kuniszyk-Jóźkowiak, W.
Smołka, E.
Kobus, A.
Powiązania:: https://bibliotekanauki.pl/articles/332965.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: sieć Kohonena
zaburzenia automatycznego rozpoznawania mowy
ciągła transformata falkowa
skala Barka
wydłużenie mowy
Kohonen network
automatic disorders speech recognition
waveblaster
CWT
continuous wavelet transform (CWT)
Bark scale
speech prolongations
Opis:: Automatic disorder recognition in speech can be very helpful for the therapist while monitoring therapy progress of the patients with disordered speech. In this article we focus on prolongations. We analyze the signal using Continuous Wavelet Transform with 18 bark scales, we divide the result into vectors (using windowing) and then we pass such vectors into Kohonen network. Quite large search analysis was performed (5 variables were checked) during which, recognition above 90% was achieved. All the analysis was performed and the results were obtained using the authors' program - "WaveBlaster". It is very important that the recognition ratio above 90% was obtained by a fully automatic algorithm (without a teacher) from the continuous speech. The presented problem is part of our research aimed at creating an automatic prolongation recognition system.
Źródło:: Journal of Medical Informatics & Technologies; 2012, 20; 137-144
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Disordered sound repetition recognition in continuous speech using CWT and Kohonen network
Autorzy:: Codello, I.
Kuniszyk-Jóźkowiak, W.
Smołka, E.
Kobus, A.
Powiązania:: https://bibliotekanauki.pl/articles/333359.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: sieć Kohonena
zaburzenia automatycznego rozpoznawania mowy
ciągła transformata falkowa
skala Barka
powtarzanie dźwięku
Kohonen network
automatic disorders speech recognition
waveblaster
CWT
continuous wavelet transform (CWT)
Bark scale
sound repetition
Opis:: Automatic disorders recognition in speech can be very helpful for therapist while monitoring therapy progress of patients with disordered speech. This article is focused on sound repetitions. The signal is analyzed using Continuous Wavelet Transform with 16 bark scales, the result is divided into vectors and passed into Kohonen network. Finally, the Kohonen winning neuron result is put on the 3-layer perceptron. The recognition ratio was increased by about 20% by adding a modification into the Kohonen network training process as well as into CWT computation algorithm. All the analysis was performed and the results were obtained using the authors' program ”WaveBlaster“, The problem presented in this article is a part of our research work aimed at creating an automatic disordered speech recognition system.
Źródło:: Journal of Medical Informatics & Technologies; 2011, 17; 123-130
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Speech nonfluency detection and classification based on linear prediction coefficients and neural networks
Autorzy:: Kobus, A.
Kuniszyk-Jóźkowiak, W.
Smołka, E.
Codello, I.
Powiązania:: https://bibliotekanauki.pl/articles/333600.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: przewidywanie liniowe
liniowe kodowanie predykcyjne
sieci nuronowe
kowariancja
brak płynności
mowa
wykrywanie
perceptron
linear prediction
LPC
neural networks
Kohonen
covariance
nonfluency
speech
detection
radial
Opis:: The goal of the paper is to present a speech nonfluency detection method based on linear prediction coefficients obtained by using the covariance method. The application “Dabar” was created for research. It implements three different methods of LP with the ability to send coefficients computed by them into the input of Kohonen networks. Neural networks were used to classify utterances in categories of fluent and nonfluent. The first one was Kohonen network (SOM), used to reduce LP coefficients representation of each window, which were used as input data to SOM input layer, to a vector of winning neurons of SOM output layer. Radial Basis Function (RBF) networks, linear networks and Multi-Layer Perceptrons were used as classifiers. The research was based on 55 fluent samples and 54 samples with blockades on plosives (p, b, d, t, k, g). The examination was finished with the outcome of 76% classifying.
Źródło:: Journal of Medical Informatics & Technologies; 2010, 15; 135-143
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Automatic disordered sound repetition recognition in continuous speech using CWT and kohonen network
Autorzy:: Codello, I.
Kuniszyk-Jóźkowiak, W.
Smołka, E.
Kobus, A.
Powiązania:: https://bibliotekanauki.pl/articles/106192.pdf
Data publikacji:: 2012
Wydawca:: Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:: speech recognition
speech disorders
sound repetition
Continuous Wavelet Transform
WaveBlaster
Opis:: Automatic disorders recognition in speech can be very helpful for a therapist while monitoring therapy progress of patients with disordered speech. This article is focused on sound repetitions. The signal is analyzed using Continuous Wavelet Transform with 16 bark scales. Using the silence finding algorithm, only speech fragments are automatically found and cut. Each cut fragment is converted into a fixed-length vector and passed into the Kohonen network. Finally, the Kohonen winning neuron result is put on the 3-layer perceptron. Most of the analysis was performer and the results were obtained using the authors’ program WaveBlaster. We use the STATISTICA package for finding the best perceptron which was then imported back into WaveBlaster and used for automatic blockades finding. The problem presented in this article is a part of our research work aimed at creating an automatic disordered speech recognition system.
Źródło:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2012, 12, 2; 39-48
1732-1360
2083-3628
Pojawia się w:: Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: A new elliptical model of the vocal tract
Autorzy:: Kobus, A.
Kuniszyk-Jóźkowiak, W.
Smołka, E.
Suszyński, W.
Codello, I.
Powiązania:: https://bibliotekanauki.pl/articles/333373.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: model eliptyczny
aparat głosowy
przewidywania liniowe
jąkanie
elliptical model
vocal tract
PARCOR
linear prediction
disfluency
stuttering
Opis:: In this paper a new model of the vocal tract is proposed. It is based on elliptical cylinders. It uses the vocal tract model based on PARCOR coefficients and midsaggital measurements of the voice tube. PARCOR coefficients were obtained from linear prediction coefficients which had been obtained by Levinson-Durbin method. Midsaggital lengths, understood as the height of a real vocal tract, were taken from X-Ray pictures, and they were averaged from the vocal tracts of a few people, who uttered the same vowels. The paper bases on Polish vowels: a,e,o,u,i,y.
Źródło:: Journal of Medical Informatics & Technologies; 2011, 17; 131-139
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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