DocumentCode :
1141172
Title :
Multiclass MTS for Saxophone Timbre Quality Inspection Using Waveform-shape-based Features
Author :
Hsiao, Yu-Hsiang ; Su, Chao-Ton
Author_Institution :
Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu
Volume :
39
Issue :
3
fYear :
2009
fDate :
6/1/2009 12:00:00 AM
Firstpage :
690
Lastpage :
704
Abstract :
Under the highly developed automation today, the manufacture of saxophone is still a nonautomatic process and much relies on highly skilled technicians. In order to insure the timbre quality, the sound of finished saxophone must be tested in the final inspection stage. The evaluation of timbre quality mainly depends on the professional musicians´ hearing judgment; however, the sensitivity of human perception can be influenced by many factors. To improve the reliability of saxophone timbre quality inspection, an automatic multiclass timbre classification system (AMTCS) is developed and used to assist in the inspection work. The AMTCS is composed of our proposed waveform-shape-based feature extraction method in parameterization phase and multiclass Mahalanobis-Taguchi system in classification phase. The numerical experiments show that the musical instrument classification accuracy obtained by our proposed AMTCS is satisfactory. Through employing the AMTCS, strong assistance was provided to the inspection of saxophone timbre quality, and a perfect identification rate on the saxophones with different timbre quality levels is achieved. Moreover, the significant tones having impact on saxophone timbre quality can also be easily identified by AMTCS.
Keywords :
acoustic signal processing; inspection; musical instruments; production engineering computing; quality assurance; automatic multiclass timbre classification system; human perception; multiclass MTS; multiclass Mahalanobis-Taguchi system; nonautomatic process; parameterization phase; saxophone manufacture; saxophone timbre quality inspection reliability; waveform-shape-based feature extraction; waveform-shape-based features; Feature extraction; Mahalanobis–Taguchi system (MTS); feature selection; multiclass classification; musical instrument classification; saxophone; sound signal; timbre;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4419
Type :
jour
DOI :
10.1109/TSMCB.2008.2008632
Filename :
4773263
Link To Document :
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