Robust and accurate F0 estimation for reverberant speech by utilizing complex cepstrum analysis

Abstract

This paper presents comparative evaluations of 12 typical methods of estimating the fundamental frequency (F0) over huge speech-sound datasets in reverberant environments. They involve several classical algorithms such as cepstrum, AMDF, LPC, and autocorrelation methods. Other methods involve a few modern algorithms, i.e., instantaneous amplitude and/or frequency-based algorithms, such as TEMPO, IFHC, and PHIA. The comparative results revealed that the percentage of correct rates and SNRs of the estimated F0s were reduced drastically as reverberation time increased. This paper, thus, proposes a method of robustly and accurately estimating F0 in reverberant environments by utilizing the MTF concept and the source-filter model in complex cepstrum analysis. The MTF concept is used in this method to eliminate dominant reverberant characteristics from observed reverberant speech. The source-filter model is used to extract source information from the processed cepstrum. Finally, F0s are estimated from them by using the comb-filtering method. Additive-comparative evaluation was carried out on the proposed method and other typical methods. The results demonstrated that it was better than the previously reported methods in terms of robustness and in providing accurate F0 estimates in reverberant environments. [Work supported by a Grant-in-Aid for Science Research from the Japanese Ministry of Education No. 18680017.]

Comparative evaluations of robust and accurate F0 estimates in reverberant environments

“…The last issue seems to be have been solved at this time; however, there have been no studies on robustness in realistic reverberant environments. In our study on simulations [7], we found that no typical methods worked as well in artificial reverberant environments and their percentage correct rates for F0s were reduced drastically as reverberation time increased. We thus proposed a method of estimating F0 from reverberant speech by utilizing the MTF concept and the source-filter model in complex cepstrum analysis [7].…”

“…In our study on simulations [7], we found that no typical methods worked as well in artificial reverberant environments and their percentage correct rates for F0s were reduced drastically as reverberation time increased. We thus proposed a method of estimating F0 from reverberant speech by utilizing the MTF concept and the source-filter model in complex cepstrum analysis [7]. However, the method then proposed was only evaluated in artificial reverberant environments (stochastic approximation).…”

“…We found the following useful facts in our previous work [7]: can establish how much reverberation affects a reduction in the modulation index and we can then predict the characteristics of room acoustics (TR) using inverse MTF. Therefore, we can easily predict that CH,A(q, τ ) will become a cepstral shape which exponential decay with respect to quefrency.…”

Estimation and tracking of fundamental, 2nd and 3d harmonic frequencies for spectrogram normalization in speech recognition

“…(8), (9). Same weighted average computation is adopted for estimating the 2nd and 3d harmonic frequencies by using related particles.…”

“…Most F 0 estimation methods are based on autocorrelation, the amplitude magnitude difference function (AMDF), the cepstrum analysis or linear prediction (LP or PARCOR) [7][8][9][10][11]. They are very effective for a noiseless target speech.…”