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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chien, Yu-Ren Jeng, Shyh-Kang |
| Copyright Year | 2002 |
| Description | Author affiliation: National Taiwan University, Graduate Institute of Communication Engineering and Department of Electrical Engineering, Taipei 10617, Taiwan, ROC (Chien, Yu-Ren; Jeng, Shyh-Kang) |
| Abstract | Octave detection has been an open issue in automatic transcription of polyphonic music over the years. In the literature, pitch detectors for polyphonic music usually fail to detect octaves for lack of information about the timbre of each instrument that appears in the music. To reveal the possibility that this difficulty in automatic music transcription can be overcome, here a music transcription system that is capable of octave detection is proposed. Preceded by a constant-Q time-frequency analysis front end implemented with a fast algorithm for nonorthonormal discrete wavelet transform [1], a classifier using support vector machine technique [2] serves as a novel octave detector in this system. |
| File Size | 844213 |
| File Format | |
| ISBN | 0780374029 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2002.5744990 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-05-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Feature extraction Finite impulse response filter Transforms Peak to average power ratio Psychoacoustics |
| Content Type | Text |
| Resource Type | Article |
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