DocumentCode :
393954
Title :
Musical instruments recognition using hidden Markov model
Author :
Lee, Jonghyun ; Chun, Joohwan
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
Volume :
1
fYear :
2002
fDate :
3-6 Nov. 2002
Firstpage :
196
Abstract :
A new musical instrument recognition technique based on a hidden Markov model (HMM) is proposed. The spectral envelope is the key information of instrument characteristic and timbre. We decompose an instrument sound into sinusoidal components (harmonics) and noise components and estimate the amplitudes of the harmonics component. We want to express the spectral envelope effectively using estimated amplitude, therefore, we define three kinds of features and apply a recognition procedure to each feature. The HMM model used is continuous single Gaussian output HMM. To evaluate the performance of the recognition technique, the proposed technique is applied to classify the real instrumental sound of MUMS (MacGill University Master Samples). The recognition success ratio is more than 70%.
Keywords :
Gaussian processes; acoustic signal processing; hidden Markov models; musical acoustics; musical instruments; pattern recognition; spectral analysis; HMM; MUMS; MacGill University Master Samples; continuous single Gaussian output; estimated amplitudes; hidden Markov model; instrument characteristics; instrument timbre; musical instrument recognition; recognition success ratio; sinusoidal components; spectral envelope; Acoustic noise; Amplitude estimation; Frequency estimation; Frequency synthesizers; Hidden Markov models; Instruments; Noise level; Phase noise; Sampling methods; Stochastic resonance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
ISSN :
1058-6393
Print_ISBN :
0-7803-7576-9
Type :
conf
DOI :
10.1109/ACSSC.2002.1197175
Filename :
1197175
Link To Document :
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