Analysis and Signal Processing of Oesophageal and Pathological Voices
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Editorial Analysis and Signal Processing of Oesophageal and Pathological Voices ´ Juan Ignacio Godino-Llorente,1 Pedro Gomez-Vilda (EURASIP Member),2 and Tan Lee3 1 Department
of Circuits & Systems Engineering, Universidad Polit´ecnica de Madrid, Carretera Valencia Km 7, 28031, Madrid, Spain of Computer Science & Engineering, Universidad Polit´ecnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28660, Madrid, Spain 3 Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong 2 Department
Correspondence should be addressed to Juan Ignacio Godino-Llorente, [email protected] Received 29 October 2009; Accepted 29 October 2009 Copyright © 2009 Juan Ignacio Godino-Llorente et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction Speech not only is limited to the process of communication but also is very important for transferring emotions, it is a small part of our personality, reflects situations of stress, and has a cosmetic added value in many different professional activities. Since speech communication is fundamental to human interaction, we are moving toward a new scenario where speech is gaining greater importance in our daily lives. On the other hand, modern styles of life have increased the risk of experiencing some kind of voice alterations. In this sense, the National Institute on Deafness and Other Communication Disorders (NIDCD) pointed out that approximately 7.5 million people in the United States have trouble using their voices [1]. Even though providing statistics on people affected by voice disorders is a very difficult task, as reported in [2], it is underlined that between 5 and 10% of the US working population have to be considered as using their voice in an intensive way. In Finland, these statistics are estimated close to 25%. Still in [2], the conclusions point out that the voice is the primary tool for about 25 to 33% of the working population. While the case of teachers has been largely studied in literature [2, 3], singers, doctors, lawyers, nurses, (tele-)marketer people, professional trainers, and public speakers also make great demands on their voices and, consequently, they are prone to experiencing voice problems [1, 4–6]. Therefore, in addition to medical consequences in daily life (treatment, rehabilitation, etc.), some voice disorders have also severe consequences regarding professional (job performance, attendance, occupation changes)
and economical aspects but also far from being negligible, regarding social activities, and interaction with others [2–4]. However, despite many years of effort devoted to developing algorithms for speech signal processing, and despite the elaboration of automatic speech recognition and synthesis systems, our knowledge of the nature of the speech signal and the effects of pathologies is still limited. In spite of this,
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