A new elliptical model of the vocal tract

• Autorzy: Kobus A. , Kuniszyk-Jóźkowiak W. , Smołka E. , Suszyński W. , Codello I.
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

elliptical model; vocal tract; PARCOR; linear prediction; disfluency; stuttering

PL

model eliptyczny; aparat głosowy; przewidywania liniowe; jąkanie

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2011
• Tom: Vol. 17
• Strony: 131--139
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Kobus A.

• Institute of Computer Science, Marie Curie–Skłodowska University, Poland

autor

Kuniszyk-Jóźkowiak W.

autor

Smołka E.

autor

Suszyński W.

autor

Codello I.

Bibliografia

• [1] CODELLO I., KUNISZYK-JÓŹKOWIAK W., Digital signals analysis with the LPC method, Annales UMCS Informatica, Vol. 5, Lublin, 2006, pp. 315n.
• [2] IZWORSKI A., TADEUSIEWICZ R., WSZOŁEK W., Artificial intelligence methods in diagnostics of the pathological speech signals, Lecture Notes in Computer Science, Vol. 3215, 2004, DOI: 10.1007/978-3-540-30134-9 99, pp. 740–748.
• [3] IZWORSKI A., TADEUSIEWICZ R., System for intelligent processing and recognition of auditory brainstem response (ABR) signals, Lecture Notes in Computer Science, Vol. 2690, 2003, DOI: 10.1007/978-3-540-45080-1 67, pp. 482-489.
• [4] HORZYK A., TADEUSIEWICZ R., Self-optimizing neural networks, Lecture Notes in Computer Science, Vol. 3173, 2004, DOI: 10.1007/978-3-540-28647-9 26, pp. 150-155.
• [5] KARCZMARCZUK B., Wymowa polska z ćwiczeniami, Wydawnictwo Polonia, Lublin, 1986, (in Polish).
• [6] KOBUS A., KUNISZYK-JÓŹKOWIAK W., SMOŁKA E., CODELLO I., Speech nonfluency detection and classification based on linear prediction coefficients and neural networks, Journal of Medical Informatics & Technologies, Vol. 15, ISSN 1642-6037, 2010, pp. 135–144.
• [7] KUNISZYK-JÓŹKOWIAK W., SUSZYŃSKI W., WARCHOŁ J., Spektrograficzna analiza niepłynności mowy, Logopedia 25, Lublin, 1998, pp. 37-47.
• [8] LYONS R., Wprowadzenie do cyfrowego przetwarzania sygnałów, WKŁ, Warszawa, 2003, (in Polish).
• [9] MAKHOUL J., Stable and efficient lattice methods for linear prediction, Proc. Of IEEE, 1970.
• [10] MARKEL J., GRAY A., Linear Prediction of Speech, Springer Verlag, Berlin, 1976.
• [11] PROKSA R., Visualization of stages of determining cepstral factors in speech recognition, Journal of Medical Informatics & Technologies, Vol. 13, ISSN 1642-6037, 2009, pp. 121–128.
• [12] RABIBER L., SCHAFER R, Digital Processing of Speech Signals, Prentice Hall, New Jersey, 1978, pp. 396-461.
• [13] SMOŁKA E., KUNISZYK-JÓŹKOWIAK W., DZIEŃKOWSKI M., SUSZYŃSKI W., ŚWIETLICKI M., Rozpoznawanie samogłosek w izolacji i mowie ciągłej z wykorzystaniem perceptronu wielowarstwowego, Biomedical Engineering, Kraków, 2005, pp. 143-148, (in Polish).
• [14] SMOŁKA E., KUNISZYK-JÓŹKOWIAK W., SUSZYŃSKI W., DZIEŃKOWSKI M., SZCZUROWSKA I., Speech nonfluency recognition in two stages of Kohonen networks, Structures Waves - Human Health (ed. R. Panuszka), Vol. XIII, No. 2, Kraków, 2004, pp. 139-142.
• [15] SZCZUROWSKA I., KUNISZYK-JÓŹKOWIAK W., SMOŁKA E., Speech nonfluency detection using Kohonen networks, Neural Computing & Applications, London, 2009.
• [16] TADEUSIEWICZ R., About usefulness of neural networks in electrical engineering problems, Electrical Review (Przeglad Elektrotechniczny), Vol. 85, Nr. 2, ISSN 0033-2097, 2009, pp. 200-211.
• [17] TADEUSIEWICZ R., Sieci neuronowe, Akademicka Oficyna Wydawnicza RM, Warszawa, 1993, (in Polish).
• [18] WIŚNIEWSKI M., KUNISZYK-JÓŹKOWIAK W., SMOŁKA E., SUSZYŃSKI W., Improved Approach to automatic detection of speech disorders based on the hidden Markov Models Approach, Journal of Medical Informatics & Technologies, Vol. 15, ISSN 1642-6037, 2010, pp. 145–152.
• [19] ZIELIŃSKI A., Teoria przetwarzania sygnałów, Wydział EAIiE AGH, Kraków, 2000 (in Polish).