Estimation Of The Source-Filter Model Using Temporal Dynamics

2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6(2007)

引用 3|浏览10
暂无评分
摘要
Sound production process is often expressed by a source-filter model, which assumes that sound signals are generated by convolution of a source signal and a synthesis filter. Although the source-filter model has been widely used, simultaneous estimation of source signals and synthesis filters is difficult due to its inherent indeterminacy. To reduce the indeterminacy, we propose a state-space model that utilizes temporal continuity of pitch and loudness. From the assumption that the synthesis filter contains the timbre-like instrument-specific features while the source signal represents time-variant components such as pitch and loudness, we can estimate the parameters of the synthesis filter and use them for instrument identification. The instrument identification experiments showed comparable or higher accuracy than the existing instrument identification methods with less number of parameters. This result supports the possibility to develop a reliable estimation method of a dynamic source-filter model.
更多
查看译文
关键词
loudness,production process,audio signal processing,state space model,feature extraction,probability,estimation theory,convolution,pitch
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要