Automatic Assessment of Voice Quality According to the GRBAS Scale
Nowadays, the most extended techniques to measure the voice quality are based on perceptual evaluation by well trained professionals. The GRBAS scale is a widely used method for perceptual evaluation of voice quality. The GRBAS scale is widely used in Japan and there is increasing interest in both E...
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| creator | Saenz-Lechon, N. Godino-Llorente, J.I. Osma-Ruiz, V. Blanco-Velasco, M. Cruz-Roldan, F. |
| description | Nowadays, the most extended techniques to measure the voice quality are based on perceptual evaluation by well trained professionals. The GRBAS scale is a widely used method for perceptual evaluation of voice quality. The GRBAS scale is widely used in Japan and there is increasing interest in both Europe and the United States. However, this technique needs well-trained experts, and is based on the evaluator's expertise, depending a lot on his own psycho-physical state. Furthermore, a great variability in the assessments performed from one evaluator to another is observed. Therefore, an objective method to provide such measurement of voice quality would be very valuable. In this paper, the automatic assessment of voice quality is addressed by means of short-term Mel cepstral parameters (MFCC), and learning vector quantization (LVQ) in a pattern recognition stage. Results show that this approach provides acceptable results for this purpose, with accuracy around 65% at the best |
| doi_str_mv | 10.1109/IEMBS.2006.260603 |
| format | Conference Proceeding |
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Godino-Llorente, J.I. ; Osma-Ruiz, V. ; Blanco-Velasco, M. ; Cruz-Roldan, F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c310t-39467e51fcce3597029ffa9c8e4e0384dbe956356a16d35527ce5123625b7f983</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Circuits</topic><topic>Cities and towns</topic><topic>Convergence</topic><topic>Diagnosis, Computer-Assisted - methods</topic><topic>Humans</topic><topic>Morphology</topic><topic>Pathology</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Protocols</topic><topic>Psychoacoustic models</topic><topic>Psychology</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Severity of Illness Index</topic><topic>Sound Spectrography - methods</topic><topic>Speech analysis</topic><topic>Speech Production Measurement - methods</topic><topic>USA Councils</topic><topic>Voice Disorders - classification</topic><topic>Voice Disorders - diagnosis</topic><topic>Voice Quality</topic><toplevel>online_resources</toplevel><creatorcontrib>Saenz-Lechon, N.</creatorcontrib><creatorcontrib>Godino-Llorente, J.I.</creatorcontrib><creatorcontrib>Osma-Ruiz, V.</creatorcontrib><creatorcontrib>Blanco-Velasco, M.</creatorcontrib><creatorcontrib>Cruz-Roldan, F.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saenz-Lechon, N.</au><au>Godino-Llorente, J.I.</au><au>Osma-Ruiz, V.</au><au>Blanco-Velasco, M.</au><au>Cruz-Roldan, F.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Automatic Assessment of Voice Quality According to the GRBAS Scale</atitle><btitle>2006 International Conference of the IEEE Engineering in Medicine and Biology Society</btitle><stitle>IEMBS</stitle><addtitle>Conf Proc IEEE Eng Med Biol Soc</addtitle><date>2006-01-01</date><risdate>2006</risdate><volume>2006</volume><spage>2478</spage><epage>2481</epage><pages>2478-2481</pages><issn>1557-170X</issn><isbn>9781424400324</isbn><isbn>1424400325</isbn><abstract>Nowadays, the most extended techniques to measure the voice quality are based on perceptual evaluation by well trained professionals. 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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithms Artificial Intelligence Circuits Cities and towns Convergence Diagnosis, Computer-Assisted - methods Humans Morphology Pathology Pattern Recognition, Automated - methods Protocols Psychoacoustic models Psychology Reproducibility of Results Sensitivity and Specificity Severity of Illness Index Sound Spectrography - methods Speech analysis Speech Production Measurement - methods USA Councils Voice Disorders - classification Voice Disorders - diagnosis Voice Quality |
| title | Automatic Assessment of Voice Quality According to the GRBAS Scale |
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