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Research on Music Retrieval Based on Content

Author: HuaHui
Tutor: LiuChuanCai
School: Nanjing University of Technology and Engineering
Course: Applied Computer Technology
Keywords: Content - based music retrieval Endpoint detection DTW algorithm Bayesian decision Melody matching algorithm
CLC: TP391.3
Type: Master's thesis
Year: 2008
Downloads: 151
Quote: 0
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Humming - based music retrieval system , the user simply hum the melody sing a song fragment into the microphone , you can get the music you want to retrieve . In the field of pattern recognition , music retrieval algorithm to get more and more attention because of its easy and efficient features , which humming sound endpoint detection , feature extraction , the music melody matching , and processing of environmental noise is music retrieval the difficulty . This paper mainly around the content - based music retrieval to carry out research work as follows : ( 1) Feature Extraction : analysis of the audio signal of the characteristics of the time domain and frequency domain characteristics , and different combinations of features to be applied to different types of audio retrieval . ( 2) endpoint detection : the traditional endpoint detection method based on endpoint detection algorithm based on Bayesian decision , but also to achieve a zero rate of endpoint detection algorithm based energy tracking endpoint detection algorithms, and center cut Bohou Ji . Experiments to compare the three algorithms to verify the validity of the endpoint detection algorithm based on Bayesian decision , to achieve a better note segmentation . (3) The pitch extraction : In traditional endpoint detection method based on the use of the autocorrelation function of the pitch period of the voiced speech segment extracted . (4) the melody matching algorithm : discourse analysis based on the format of the music data classification , respectively characteristic the melody feature matching algorithm by the DTW algorithm melody match . The music signal by the endpoint detection note segmentation, to improve the accuracy of the notes feature extraction . On the basis of the endpoint detection , improved DTW, significantly improves the recognition results .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Retrieval machine
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