Bark-shift based nonlinear speaker normalization using the second subglottal resonance
نویسندگان
چکیده
In this paper, we propose a Bark-scale shift based piecewise nonlinear warping function for speaker normalization, and a joint frequency discontinuity and energy attenuation detection algorithm to estimate the second subglottal resonance (Sg2). We then apply Sg2 for rapid speaker normalization. Experimental results on children’s speech recognition show that the proposed nonlinear warping function is more effective for speaker normalization than linear frequency warping. Compared to maximum likelihood based grid search methods, Sg2 normalization is more efficient and achieves comparable or better performance, especially for limited normalization data.
منابع مشابه
Automatic detection of the second subglottal resonance and its application to speaker normalization.
Speaker normalization typically focuses on inter-speaker variabilities of the supraglottal (vocal tract) resonances, which constitute a major cause of spectral mismatch. Recent studies have shown that the subglottal airways also affect spectral properties of speech sounds, and promising results were reported using the subglottal resonances for speaker normalization. This paper proposes a reliab...
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