DocumentCode :
1347283
Title :
Genre classification system of TV sound signals based on a spectrogram analysis
Author :
Han, Kyu-Phil ; Park, Young-Sik ; Jeon, Seong-Gyu ; Lee, Gwang-Choon ; Ha, Yeong-Ho
Author_Institution :
Sch. of Electron. & Electr. Eng., Kyungpook Nat. Univ., Taegu, South Korea
Volume :
44
Issue :
1
fYear :
1998
fDate :
2/1/1998 12:00:00 AM
Firstpage :
33
Lastpage :
42
Abstract :
A genre classification system of TV sound signals is proposed to provide a proper timbre automatically to the listener. The spectral and temporal properties of TV sound are analyzed using the spectrogram principle to classify the genre. Some acoustic features such as the frequency distribution, energy variation, etc. are extracted for classification. The sound is first classified into speech or music signals and the music signals are again divided into popular, jazz, or classical mode. After the classification, the frequency gain of the sound is regulated by the existing compensation data according to the genre. The proposed system is implemented using 7 bandpass filters, an 8-bit microprocessor, and a threshold circuit for calculating the silence interval of the signal. From the experimental results, the classification accuracy of speech and music was 95%, and the accuracy between popular, jazz, and classical music was 75%, 30%, and 60%, respectively
Keywords :
acoustic signal processing; audio signals; band-pass filters; digital signal processing chips; feature extraction; microprocessor chips; music; spectral analysis; speech processing; television receivers; video signal processing; 8 bit; TV set; TV sound signals; acoustic features extraction; bandpass filters; classical music; classification accuracy; compensation data; energy variation; experimental results; frequency distribution; frequency gain; genre classification system; jazz; microprocessor; music signals; popular music; silence interval; spectral properties; spectrogram analysis; speech signals; temporal properties; threshold circuit; timbre; Band pass filters; Data mining; Frequency; Microprocessors; Multiple signal classification; Music; Spectrogram; Speech; TV; Timbre;
fLanguage :
English
Journal_Title :
Consumer Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-3063
Type :
jour
DOI :
10.1109/30.663728
Filename :
663728
Link To Document :
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