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Robust Voicing Detection and \(F_{0}\) Estimation for HMM-Based Speech Synthesis

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Abstract

This paper proposes a robust voicing detection and \(F_{0}\) estimation method for Hidden Markov model (HMM)-based speech synthesis system. Impulse-like excitation present in voiced speech is utilized for extracting the fundamental frequency. Zero-frequency filter (ZFF) is used to derive the locations of impulse excitation. The main contribution of this paper is exploitation of size of window used in ZFF for accurate voicing detection and \(F_{0}\) estimation. By adaptively choosing appropriate window size, the strength of excitation for voiced speech is significantly higher compared with unvoiced speech. With suitable threshold on the strength of excitation, accurate voicing detection is performed. In this method, smooth and accurate \(F_{0}\) contour is extracted by frame-wise zero-frequency filtering of speech with appropriate window size. Performance of the proposed method is compared with other existing voicing detection and \(F_{0}\) estimation methods. The proposed voicing detection and \(F_{0}\) estimation method is implemented in HMM-based speech synthesis system. Both objective and subjective evaluation results show that the proposed method is capable of generating good quality speech compared with HMM-based speech synthesis systems developed using voicing detection and \(F_{0}\) estimation methods based on Robust algorithm for pitch tracking and Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum.

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Acknowledgments

The authors would like to thank Dr. Nagarajan T and his students at the speech laboratory of SSN College of Engineering for organizing workshop on HMM-based speech synthesis system. They are greatfull to Prof. Hema A Murthy and Dr. K. Samudravijaya for their precious help in understanding HMM-based speech synthesis system. The authors would also like to thank Department of Information Technology, Government of India for sponsoring the workshop on HMM-based speech synthesis system.

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  1. School of Information Technology, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    N. P. Narendra & K. Sreenivasa Rao

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Correspondence to N. P. Narendra.

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Narendra, N.P., Rao, K.S. Robust Voicing Detection and \(F_{0}\) Estimation for HMM-Based Speech Synthesis. Circuits Syst Signal Process 34, 2597–2619 (2015). https://doi.org/10.1007/s00034-015-9977-8

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