Journal ArticleDOI
Experiments with fast Fourier transform, linear predictive and cepstral coefficients in dysarthric speech recognition algorithms using hidden Markov model
P.D. Polur,G.E. Miller +1 more
- Vol. 13, Iss: 4, pp 558-561
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TLDR
The hidden Markov Model constructed and conditions investigated that would provide improved performance for a dysarthric speech (isolated word) recognition system found that a Mel cepstrum based model outperformed a fast Fourier transform and linear prediction based model.Abstract:
In this study, a hidden Markov Model was constructed and conditions were investigated that would provide improved performance for a dysarthric speech (isolated word) recognition system. The speaker dependant system was intended to act as an assistive/control tool. A small size vocabulary spoken by three cerebral palsy subjects was chosen. Fast Fourier transform, linear predictive, and Mel frequency cepstral coefficients extracted from data provided training input to several whole-word hidden Markov model configurations. The effect of model structure, number of states, and frame rates were also investigated. It was noted that a 10-state ergodic model using 15 msec frames was better than other configurations. Furthermore, it was found that a Mel cepstrum based model outperformed a fast Fourier transform and linear prediction based model. The system offers effective and robust application as a rehabilitation and/or control tool to assist dysarthric motor impaired individuals.read more
Citations
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Journal ArticleDOI
A speech-controlled environmental control system for people with severe dysarthria.
Mark S. Hawley,Pam Enderby,Phil D. Green,Stuart Cunningham,Stuart Cunningham,Simon Brownsell,James Carmichael,Mark Parker,Athanassios Hatzis,P. O'Neill,Rebecca Palmer,Rebecca Palmer +11 more
TL;DR: It is concluded that a speech-controlled ECS is a viable alternative to switch-scanning systems for some people with severe dysarthria and would lead, in many cases, to more efficient control of the home.
Journal ArticleDOI
Silent Speech Recognition as an Alternative Communication Device for Persons With Laryngectomy
Geoffrey S. Meltzner,James T. Heaton,Yunbin Deng,Gianluca De Luca,Serge H. Roy,Joshua C. Kline +5 more
TL;DR: This study provides a compelling proof-of-concept for sEMG-based alaryngeal speech recognition, with the strong potential to further improve recognition performance.
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Statistical Pattern Recognition and Built-in Reliability Test for Feature Extraction and Health Monitoring of Electronics under Shock Loads
TL;DR: In this paper, a new approach has been developed to monitor product-level damage during shock and vibration using the dynamic response of the electronic equipment, which is applicable at the system level for identification of impending failures to trigger repair or replacement significantly prior to failure.
Journal ArticleDOI
Artificial neural networks as speech recognisers for dysarthric speech: Identifying the best-performing set of MFCC parameters and studying a speaker-independent approach
TL;DR: This paper studies the application of ANNs as a fixed-length isolated-word SI ASR for individuals who suffer from dysarthria and identifies the best-performing set of MFCC parameters, which can represent dysarthric acoustic features to be used in Artificial Neural Network (ANN)-based ASR.
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An SVD audio watermarking approach using chaotic encrypted images
Waleed Al-Nuaimy,Mohsen A. M. El-Bendary,Amira Shafik,F. Shawki,A. E. Abou-El-azm,Nawal El-Fishawy,S. M. Elhalafawy,Salaheldin M. Diab,B. M. Sallam,Fathi E. Abd El-Samie,Hassan B. Kazemian +10 more
TL;DR: Experimental results show that the proposed audio watermarking approach maintains the high quality of the audio signal and that the watermark extraction and decryption are possible even in the presence of attacks.
References
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