Paper
18 April 2003 Signals voice biofeedback for speech fluency disorders
Jose Francisco Martin, Raquel Fernandez-Ramos, Jorge Romero-Sanchez, Francisco Rios
Author Affiliations +
Proceedings Volume 5119, Bioengineered and Bioinspired Systems; (2003) https://doi.org/10.1117/12.499047
Event: Microtechnologies for the New Millennium 2003, 2003, Maspalomas, Gran Canaria, Canary Islands, Spain
Abstract
The knowledge about mechanisms of voice production as well as the parameters obtaining, allow us to present solutions for coding, transmission and establishment of properties to distinguish between the responsible physiological mechanisms. In this work, we are interested in the evaluation of syllabic Sequences in Continuous Speech. We keep in mind this evaluation is very interesting and useful for Foniatrics and Logopaedia applications focus on the measurement and control of Speech Fluency. Moreover, we are interested in studying and evaluating sequential programming and muscular coordination. In this way, the main objective of our work is focus on the study of production mechanisms, model, evaluation methods and introduction of a reliable algorithm to catalogue and classify the phenomena of rythm and speech fluency. In this paper, we present an algorithm for syllabic analysis based on Short Time Energy concept. Firstly, the algorithm extracts the temporary syllabic intervals of speech and silence, and then compared with normality intervals. Secondly, it proceeds to feedback in real time to the patient luminous and acoustic signals indicating the degree of mismatching with the normality model. This methodology is useful to improve fluency disorder. We present an ASIC microelectronic solution for the syllabic analyser and a portable prototype to be used in a clinic level as much as individualized tool for the patient.
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Jose Francisco Martin, Raquel Fernandez-Ramos, Jorge Romero-Sanchez, and Francisco Rios "Signals voice biofeedback for speech fluency disorders", Proc. SPIE 5119, Bioengineered and Bioinspired Systems, (18 April 2003); https://doi.org/10.1117/12.499047
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KEYWORDS
Detection and tracking algorithms

Acoustics

Prototyping

Signal to noise ratio

Digital signal processing

Algorithm development

Biological research

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