Vibrato Detection for Monophonic Vocals And Polyphonic Music

• Main Authors: Deng, Kai, 鄧愷
• Other Authors: 張智星
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/09585962627189544382

碩士 === 國立清華大學 === 資訊工程學系 === 101 === Vibrato is a musical effect consisting of a regular, pulsating change of pitch. It includes the extent of vibrato and the rate of vibrato. Vibrato always appears in folk and opera. This thesis is to explore the feasible method for feature extraction, and experiment some kinds of classifier, then build an reliable solution of vibrato detection. The research thesis includes "vibrato detection for monophonic vocals" and "vibrato detection for polyphonic music". Hoped to get the better recognition rate, we try the different case of feature extraction and classifier in the two cases. At first in "vibrato detection for monophonic vocals", we do feature selection with pitch and volume. By sine fit, get the amplitude, frequency and error of the pulsating change. Do experiments such as feature selection and so on, then get the better feature. Get the recognition rates and area under curve (AUC) of static classifier, compare the result with hidden Markov model (HMM), try to get the appropriate classifier. Then in "vibrato detection for polyphonic music", pitch tracking cannot be accurate. It needs to found new method for feature extraction. Low level descriptor (LLD) and delta regression coefficients is used to extract some feature about extreme, moments, Discrete Cosine Transform, Discrete Fournier Transform and so on. Do some experiment to select appropriate features and find the appropriate classifier.