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基于谐波结构信息的自动音乐标注方法 被引量:4

Automatic Music Transcription Based on Harmonic Structure Information
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摘要 根据同类乐器音色相似的特点,提出了一种基于谐波结构信息的自动音乐标注方法·该方法事先提取一类乐器中某一件乐器的谐波结构信息·根据输入信号选择合适的不谐和系数、频率误差系数,结合谐波结构信息构造同类未知乐器的响度谱,然后采用截断完全最小二乘法实现对同类未知乐器音乐的标注·对钢琴音乐的实验证明,该方法不仅能对未知乐器的音乐进行标注,取得较好的性能,还可辨别音符的响度强弱· A novel method for automatic music transcription based on harmonic structure information is developed in this paper. The instruments of the same class have similar timber and harmonic structure. Therefore, harmonic structure information of an instrument is acquired beforehand and is used to construct the loudness spectrum for the unknown instrument of the same class in music transcription. The inharmonicity factor and the error in note fundamental frequency are considered during the spectrum construction. The loudness spectrum of input audio can be considered approximately as the linear sum of spectra corresponding to the mixed notes and the truncated total least squares is used to solve the sum equation. Experimental results of piano music transcription show that the method not only can transcribe music of an unknown instrument with high performance, but also can distinguish the loudness of mixed notes.
出处 《计算机研究与发展》 EI CSCD 北大核心 2006年第12期2187-2192,共6页 Journal of Computer Research and Development
基金 国家自然科学基金委员会与微软亚洲研究院联合资助项目(60672163) 国家自然科学基金项目(60575030) 哈尔滨市重点科技攻关基金项目(2005AA1CG036)~~
关键词 音乐标注 谐波结构信息 响度 截断完全最小二乘法 music transcription harmonic structure information loudness truncated total least squares
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参考文献13

  • 1M D Plumbley,S A Abdallah,J P Bello,et al.Automatic music transcription and audio source separation[J].Cybernetics and Systems,2002,33(6):603-627
  • 2J A Moorer.On the segmentation and analysis of continuous musical sound by digital computer:[Ph D dissertation][D].San Francisco,CA:Stanford University,1975
  • 3T Tolonen,M Karjalainen.A computationally efficient multipitch analysis model[J].IEEE Trans on Speech and Audio Processing,2000,8(6):708-716
  • 4M Goto.A predominant-F0 estimation method for CD recordings:MAP estimation using EM algorithm for adaptive tone models[C].IEEE Int'l Conf on Acoustics,Speech,and Signal Processing,Salt Lake City,Utah,2001
  • 5C Raphael.Automatic transcription of piano music[C].The 3rd Int'l Conf on Musical Information Retrieval,Baltimore,Maryland,2002
  • 6A de Cheveigne,H Kawahara.Multiple period estimation and pitch perception model[J].Speech Communication,1999,27(3):175-185
  • 7A Klapuri.Automatic transcription of music[C].The Stockholm Music Acoustics Conf.Stockholm,Sweden,2003
  • 8I Barbancho,A M Barbancho,A Jurado,et al.Transcription of piano recordings[J].Applied Acoustics,2004,65(12):1261-1287
  • 9J Yin,T Sim,Y Wang,et al.Music transcription using an instrument model[C].IEEE Int'l Conf on Acoustics,Speech,and Signal Processing,Philadelphia,Pennsylvania,2005
  • 10N H Fletcher,T D Rossing.The Physics of Musical Instruments (2nd edition)[M].Berlin:Springer-Verlag,1998

共引文献5

同被引文献31

  • 1颜跃进,李舟军,陈火旺.一种挖掘最大频繁项集的深度优先算法[J].计算机研究与发展,2005,42(3):462-467. 被引量:20
  • 2王长富,林志钢,戴蓓倩,张劲松.基于小波变换的语音基音周期检测[J].中国科学技术大学学报,1995,25(1):47-52. 被引量:8
  • 3于拾全,景新幸,刘志国.乐器音高检测方法的比较和精度分析[J].电声技术,2006,30(7):4-7. 被引量:5
  • 4Yin J,Sim T,Wang Y,et al.Music transcription using an instrument model[C].Proceedings of IEEE International Conference on Acoustics,Speech,and Signal,2005:217-210.
  • 5Kameoka H,Nishimoto T,Sagayama S.A multipitch analyzer based on harmonic temporal structured clustering[J].IEEE Transaction on Audio,Speech and Language Procossing,2007,15(3):982-994.
  • 6Viste H,Evangelista G.A method for separation of overlapping partials based on similarity of temporal envelopes in muitichannel mixtures[J].IEEE Transactions on Audio Speech and Language Processing,2006,14(3):1051-1061.
  • 7Kitahara T,Goto M,Komatani K,et al.Instrument identification in polyphonic music:feature weighting to minimize influence of sound overlaps[J].EURASIP Journal on Advances in Signal Processing,2007(1):558-563.
  • 8Klapuri A.A perceptually motivated multiple-f0 estimation method for polyphonic music signals[C].Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics,2005:291-294.
  • 9Klapuri A.Multiple fundamental frequency estimation by summing harmonic amplitudes[C].Victoria,BC,Canada:Proceedings of 7th International Conference on Music Information Retrieval,2006:216-221.
  • 10Davy M,Godsill S.Bayesian harmonic models for musical signal analysis[C].Spain:Proceedings of 7th Valencia International Meeting on Bayesian Statistics,2003:105-124.

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