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Spectrogram Based Musical Instrument Identification Using Hidden Markov Model ( Hmm ) for Monophonic and Polyphonic Music Signals
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bhalke, D. G. Rao, C. B. Rama Bormane, Dattatraya S. Vibhute, Mahesh A. |
| Copyright Year | 2011 |
| Abstract | Spectrogram is generated for musical notes, which is used to calculate the spectral, temporal and modulation features. To detect the musical instruments from polyphonic and monophonic musical notes , 23 features are analyzed . Out of 23 features 12 specific features are used to generate feature vector . Hidden Markov model (HMM) is used to calculate the conditional instrument existence probability. In this work, ten musical instruments from wind and string categories are used for identification. The musical instruments are recognized using different HMM algorithms: Forward, Backward, Posterior decoding and Viterbi algorithm and their results are compared . Recognition accuracy achieved for monophonic musical notes are 91% and 87% for polyphonic musical notes. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://users.utcluj.ro/~atn/papers/ATN_2_2011_1.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
