Analysis and Signal Processing of Oesophageal and Pathological Voices
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Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:283504
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Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema
Two distinct two-class pattern recognition problems are studied, namely, the detection of male subjects who are diagnosed with vocal fold paralysis against male subjects who are diagnosed as normal and the det...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:203790 -
A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification
The number of people affected by speech problems is increasing as the modern world places increasing demands on the human voice via mobile telephones, voice recognition software, and interpersonal verbal commu...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:928974 -
Jitter Estimation Algorithms for Detection of Pathological Voices
This work is focused on the evaluation of different methods to estimate the amount of jitter present in speech signals. The jitter value is a measure of the irregularity of a quasiperiodic signal and is a good...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:567875 -
Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia
This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning exper...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:982102 -
Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques
This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the au...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:982531 -
On the Use of the Correlation between Acoustic Descriptors for the Normal/Pathological Voices Discrimination
This paper presents an analysis system aiming at discriminating between normal and pathological voices. Compared to literature of voice pathology assessment, it is characterised by two aspects. First the syste...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:173967 -
A First Comparative Study of Oesophageal and Voice Prosthesis Speech Production
The purpose of this work is to evaluate and to compare the acoustic properties of oesophageal voice and voice prosthesis speech production. A group of 14 Italian laryngectomized patients were considered: 7 wit...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:821304 -
Alternative Speech Communication System for Persons with Severe Speech Disorders
Assistive speech-enabled systems are proposed to help both French and English speaking persons with various speech disorders. The proposed assistive systems use automatic speech recognition (ASR) and speech sy...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:540409 -
Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals
Harmonics-to-noise ratios (HNRs) are affected by general aperiodicity in voiced speech signals. To specifically reflect a signal-to-additive-noise ratio, the measurement should be insensitive to other periodic...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:784379 -
Analysis of Acoustic Features in Speakers with Cognitive Disorders and Speech Impairments
This work presents the results in the analysis of the acoustic features (formants and the three suprasegmental features: tone, intensity and duration) of the vowel production in a group of 14 young speakers su...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:159234 -
Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers
Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed f...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:308340 -
Automated Intelligibility Assessment of Pathological Speech Using Phonological Features
It is commonly acknowledged that word or phoneme intelligibility is an important criterion in the assessment of the communication efficiency of a pathological speaker. People have therefore put a lot of effort...
Citation: EURASIP Journal on Advances in Signal Processing 2009 2009:629030