Multiband excitation vocoder

Griffin, Daniel; Lim, Jae S.

doi:10.1109/29.1651

Cited by 414 publications

(148 citation statements)

References 22 publications

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“…The second technique for spectral weighting makes use of a maximum voiced frequency (Fm) which demarcates the boundary between the periodic component (which holds only in the low frequencies) and the aperiodic component (which holds only in the high frequencies). This idea originates from the multiband excitation vocoder [28], which was was later integrated into several methods for excitation modeling in HMM-based speech synthesis [16,22].…”

Section: Noise Spectral Weightingmentioning

confidence: 99%

Excitation modeling for HMM-based speech synthesis: Breaking down the impact of periodic and aperiodic components

Drugman

Raitio

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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HMM-based speech synthesis generally suffers from typical buzziness due to over-simplified excitation modeling of voiced speech. In order to alleviate this effect, several studies have proposed various new excitation models. No consensus has however been reached on what is the perceptual importance of the accurate modeling of the periodic and aperiodic components of voiced speech, and to what extent they separately contribute in improving naturalness. This paper considers a generalized mixed excitation modeling, common to various existing approaches, in which both periodic and aperiodic components coexist. At least three main factors may alter the quality of synthesis: periodic waveform, noise spectral weighting, and noise time envelope. Based on a large subjective evaluation, the goal of this paper is threefold: i) to evaluate the relative perceptual importance of each factor, ii) to investigate what is the most appropriate method to model the periodic and aperiodic components, and iii) to provide prospective clues for future work in excitation modeling.

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Section: Noise Spectral Weightingmentioning

confidence: 99%

Excitation modeling for HMM-based speech synthesis: Breaking down the impact of periodic and aperiodic components

Drugman

Raitio

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…The estimation of the fundamental frequency has received immense interest from different speech research areas, such as speech segregation, speech synthesis, speech coding, speech and speaker recognition, and speech articulation training for the deaf (Griffin, Lim, 1988;Atal, 1972;Kawahara et al, 1999). A number of algorithms for determining the fundamental frequency has been developed.…”

Section: Previous Workmentioning

confidence: 99%

Estimation of the Fundamental Frequency of the Speech Signal Compressed by MP3 Algorithm

Milivojević¹,

Brodić

2013

Archives of Acoustics

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The paper analyzes the estimation of the fundamental frequency from the real speech signal which is obtained by recording the speaker in the real acoustic environment modeled by the MP3 method. The estimation was performed by the Picking-Peaks algorithm with implemented parametric cubic convolution (PCC) interpolation. The efficiency of PCC was tested for Catmull-Rom, Greville, and Greville twoparametric kernel. Depending on MSE, a window that gives optimal results was chosen.

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“…Complex prediction techniques were adopted, the masking properties of the human ear were exploited, and it became technologically feasible to quantize parameters in blocks (VQ-vector quantization) instead of individually, and use computationally complex analysis-by-synthesis procedures. CELP (Schroeder & Atal, 1985) multi-pulse and regular-pulse (Kroon, Deprettere, et al, 1986) excitation methods are some of the most well-known new generation coders in the time domain, whereas in the frequency domain one should mention sinusoidal/harmonic (Almeida & Silva, 1984;McAulay & Quatieri, 1986) and multi-band excited coders (Griffin & Lim, 1988). Variants of these coders have been standardized for transmission at bit rates ranging from 13 down to 4.8 Kbps, and special standards have also been derived for low-delay applications (LD-CELP) (Chen, 1991).…”

Section: Chapter Referencesmentioning

confidence: 99%