2 Personal Introduction previousnexthome end Academic Experience (1999-2006) Bachelor and Master Degree on Electrical Engineering, Zhejiang University,

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Presentation transcript:

2 Personal Introduction previousnexthome end Academic Experience ( ) Bachelor and Master Degree on Electrical Engineering, Zhejiang University, China Work Experience ( ) Audio and Speech Processing Engineer, Spreadtrum Communications Co. Ltd, Shanghai, China

3 Personal Introduction previousnexthome end Knowledge Background and Interests – Signal Processing Theories, especially on Time- Frequency Analysis and Statistical Signal Processing – Machine Learning, especially on Dimensionality Reduction, Classifier design – Speech/Audio Related Algorithm Research, Mathematics

4 On-Going Research Topic previousnexthome end

5 Accounting for Continuity in HMMs previousnexthome end Basic Idea of Our Research: Model (Time-)Continuity in a long-term feature representation Modification of Input Features: 1.From 39 MFCCs to 13L MFCCs (L is the number of frames) 2.From Vector to Matrix Representation Modification of Likelihood Computation: 1.From parametric to non-parametric models

6 Research Direction (1) previousnexthome end Using feature matrix as a unit to model observation probabilities in HMM: Motivations: Why L>3? Continuity is more obvious in a longer term Why matrix? Matrix-based features contain more information than vector-based ones because of the Time- Continuity

7 Research Direction (2) previousnexthome end Using non-parametric model for observation probability estimation: Why non-parametric model (template-matching as an example)? Parametric models in HMM do not specifically consider the time- continuity, while some non-parametric models might do.