Automatic Detection of Voice Impairments by Means of Short-Term Cepstral Parameters and Neural Network Based Detectors

IEEE Transactions on Biomedical Engineering

Volumn 51, Issue 2, 2004, Pages 380-384

  Godino Llorente, J I ^a   Gomez Vilda P ^b  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Cepstral parameters; Impaired voices; Neural networks; Short term analysis

Indexed keywords

ACOUSTIC SIGNAL PROCESSING; DISEASES; NEURAL NETWORKS; SPEECH ANALYSIS; SPEECH INTELLIGIBILITY;

LARYNGOSCOPY; SHORT-TERM CEPSTRAL PARAMETERS; VOICE IMPAIRMENTS;

BIOMEDICAL ENGINEERING;

ACCURACY; ALGORITHM; ARTICLE; AUTOANALYSIS; CALCULATION; CEPSTRAL PARAMETER; HUMAN; LARYNX CANCER; LARYNX DISORDER; LEARNING VECTOR QUANTIZATION TECHNIQUE; MEL FREQUENCY COEFFICIENT CEPSTRAL PARAMETERIZATION; MULTILAYER PERCEPTRON TECHNIQUE; NERVE CELL NETWORK; PARAMETER; RELIABILITY; SIGNAL DETECTION; TECHNIQUE;

ALGORITHMS; CLUSTER ANALYSIS; DATABASES, FACTUAL; DIAGNOSIS, COMPUTER-ASSISTED; FOURIER ANALYSIS; HUMANS; NERVE NET; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; SENSITIVITY AND SPECIFICITY; SPEECH ACOUSTICS; SPEECH PRODUCTION MEASUREMENT; VOICE DISORDERS; VOICE QUALITY;

EID: 9144269627     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2003.820386     Document Type: Article

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