PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Selected methods of pathological speech signal analysis

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Selected results of examinations, having been performed by the author for several years, concerning the evaluation of selected methods of transforming signal in analysis tasks and pathological speech evaluation usability were presented in the article. In many issues of medical diagnosis, as well as in the planning of some illnesses therapy and rehabilitation, it is necessary to evaluate the signal of deformed speech. This evaluation can concern evaluation of the signal deformation degree and in this case the task is to present in a quantitative dimension (preferably scalar) the measure of deviation between the measured pathological speech signal and the abstract signal, which can be acknowledged as a pattern of the correct speech. Possessing such a scalar measurement, of the considered signal deformation degree, enables to monitor the illness process development or remission, which has a key importance in the current monitoring of the therapy effects or/and many illnesses rehabilitation. Pathological speech evaluation can also go into the direction of a classification and determination of a type of the analysed signal, which can, in some cases, have a direct connection with anatomical and functional causes as well as conditions of the considered illness. The classification of pathological speech signals can facilitate the diagnosis by pointing the most probable causes of the speech signal pathological deformation. Such a classification can also help in the optimal therapy selection and in determining rehabilitation recommendations. The methods of transformation, analysis, classification and speech signal recognition have been known apparently for many years, as with no difficulty, many writings discussing these concepts and presenting results concerning both basic examinations results and many application works, can be found. The problem, presented in this article, is strongly different from the majority of works, which were published by other authors, as most of well known works, concerning the speech signal analysis (etc.), are directed to understand the content of the statement (automatic speech understanding, a speech-writing conversion, steering of the devices by speech signal), or relatively by determining the identity of the speaker (automatic identification or authentification of the speaker). Meanwhile, in the pathological speech analysis the semantic statement content is not essential; it is also not important who the speaker is. The research subject is the speech articulation process itself and all its pathological deformations, which determines both the used signal analysis tools as well as the techniques of the selected objects recognition, which are the forms of the particular ill person speech deformation forms in comparison to the speech of the whole sound people population [5].
Twórcy
autor
  • AGH University of Science and Technology, Faculty of Mechanical Engineering and Robotics, Department of Mechanics and Vibroacoustics, Al. Mickiewicza 30, 30-059 Kraków, Poland, wwszolek@agh.edu.pl
Bibliografia
  • [1] ADAMCZYK J. A., WSZOŁEK W., The analysis and ewaluation of machine emitted vibroacoustics signal patterns, Zeszyty Naukowe AGH, Mechanika, 9, 4, 5.15 (1990).
  • [2] DEMENKO G., Analiza cech suprasegmentalnych języka polskiego na potrzeby technologii mowy, UAM, Poznań 2000.
  • [3] ENGEL Z., MODRZEJEWSKI M., WSZOŁEK W., Akustyczna ocena operacji krtani z wykorzystaniem parametrów tonu podstawowego, Zeszyty Naukowe AGH, Mechanika, 16, 1, 1997.
  • [4] GROCHOLEWSKI S., Statystyczne podstawy systemu ARM dla języka polskiego, WPP, Poznań 2001.
  • [5] GUBRYNOWICZ R., Komputerowe modelowanie artykulacji głosek języka polskiego, IPPT PAN, Warszawa 2000.
  • [6] IZWORSKI A., TADEUSIEWICZ R., WSZOŁEK W., Artificial intelligence methods in diagnostics of the pathological speech signals, [in:] NEGOITA M. GH., HOWLETT R. J., JAIN L. C. [Eds.],
  • [7] MAKAREWICZ R., Wstęp do akustyki teoretycznej, Wyd. UAM, Poznań 2005.
  • [8] MAJEWSKI W., MYŚLECKI W., BRACHMAŃSKI S., Metody oceny jakości transmisji sygnału mowy, OSA 2000,pp. 61-72, Rzeszów . Jawor, 19-22.09.2000.
  • [9] MODRZEJEWSKI M., OLSZEWSKI E., WSZOŁEK W., RERO´N E., STREK P., Acoustic assessment of voice signal deformation after partial surgery of the larynx, Auris Nasus Larynx, International Journal of ORL & NNS, Japan, 26, 183.190 (1999).
  • [10] MODRZEJEWSKI M., OLSZEWSKI E., STREK P., WSZOŁEK W., ZIELIŃSKA J., Effectiveness of classical chordectomy in the treatment of cancer of the glottis, Auris Nasus Larynx, International Journal of ORL & NNS, Japan, 25, 59.66 (1998).
  • [11] OZIMEK E., Dźwięk i jego percepcja. Aspekty fizyczne i psychoakustyczne, Wydawnictwo Naukowe PWN, Warszawa . Poznań 2002.
  • [12] RERO´N E., TADEUSIEWICZ R., MODRZEJEWSKI M., WSZOŁEK W., Application of neural networks and pattern recognition methods to the evaluation of speech deformation degree for patients surgically treated for larynx cancer, Neuroendocrinology Letters, 19, 3, 147.157, 1998, Mattes-Heidelberg-Germany.
  • [13] SZALENIEC J., MODRZEJEWSKI M., WSZOŁEK W., Research on the influence of endotracheal intubation on the speech signal, Speech Analysis Synthesis and Recognition in Technology Linguistics and Medicine, AGH, , Krakow 2005, pp. 127-133
  • [14] TADEUSIEWICZ R., IZWORSKI A., WSZOŁEK W., WSZOŁEK T., Processing and classification of deformed speech using neural networks, Proceedings of The First Joint Meeting of BMES & EMBS Serving Humanity, Advancing Technology, 13.16 Oct., Atlanta, USA 1999.
  • [15] TADEUSIEWICZ R., IZWORSKI A., WSZOŁEK W., Pathological speech evaluation using the artificial intelligence methods, World Congress on Medical Physics and Biomedical Engineering, September 14.19, Nice, France 1997.
  • [16] WSZOŁEK W., Pewne miary stosowane w ocenie mowy zniekształconej, Mat. Konf. I Krajowa Konferencja Głosowa Komunikacja Człowiek.Komputer, pp. 201.206, Wrocław 1985.
  • [17] WSZOŁEK W., TADEUSIEWICZ R., Methods of voice signal analysis using artificial intelligence methods, Archives of Acoustics, 28, 3, 245 (2003).
  • [18] WSZOŁEK W., WSZOŁEK T., Automatic understanding of speech signal, [in:] KŁOPOTEK A., WIERZCHOŃ S., TROJANOWSKI K. [Eds.], Intelligent Information Processing and Web Mining, pp. 609.620, Springer-Verlag, Berlin . Heidelberg . New York 2004.
  • [19] WSZOŁEK W., MODRZEJEWSKI M., Methods of acoustic voice signal evaluation after ENT surgery, 1st International Conference on Experiments/Process/System Modelling/Simulation/Optimization, Athens, 6-9 July, 2005 (on CD).
  • [20] WSZOŁEK W., KŁACZYŃSKI M., Acoustic methods of voice estimation after surgical treatment of the vocal tract, Archives of Acoustics, 30, 4 (Supplement), 193.197 (2005).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT8-0003-0040
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.