Browsing by Author "Chen, Jian-Hueng"

Now showing 1 - 4 of 4

PERCEPTION-BASED OBJECTIVE SPEECH QUALITY ASSESSMENT
(2009)
Yen, Ting-Yu
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Chen, Jian-Hueng
;
Chi, Tai-Shih
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電信工程研究所
;
Institute of Communications Engineering
A joint spectro-temporal auditory model is utilized to assess speech quality objectively. The model mimics early and central auditory functions and serves as a spectro-temporal modulation filterbank. Three perceptual relevant parameters, intelligibility, clarity and naturalness, are addressed by the model and are combined to estimate the subjective mean opinion score (MOS) for speech quality measure. Through a simple multiple linear regression analysis, we demonstrate the performance of our proposed perception-based objective speech quality measure is better than that of the state-of-the-art P.563 standard in estimating MOS of the codec-distorted speech in ITU-T Supp. 23 database.
Spectro-temporal Modulation Based Singing Detection Combined with Pitch based Grouping for Singing Voice Separation
(2013-01-01)
Lin, Tse-En
;
Hsu, Chung-Chien
;
Chen, Yi-Cheng
;
Chen, Jian-Hueng
;
Chi, Tai-Shih
A spectro-temporal modulation based singing voice detection cascaded with a Viterbi based pitch tracking algorithm is proposed in this paper for singing-voice separation from monaural recordings. To detect the singing voice, the spectrotemporal modulation energy related to voice harmonics is extracted using a spectro-temporal modulation analysis framework developed for the Fourier spectrogram. Separation of singing -voice from background music is conducted using a binary mask to group estimated harmonics of singing voice. The proposed system is evaluated using MIR-1K dataset and is shown outperforming three other binary-mask based systems in the vocal/music separation task.
SPECTRO-TEMPORAL SUBBAND WIENER FILTER FOR SPEECH ENHANCEMENT
(2012)
Hsu, Chung-Chien
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Lin, Tse-En
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Chen, Jian-Hueng
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Chi, Tai-Shih
;
電子工程學系及電子研究所
In this paper, we propose a signal-channel speech enhancement algorithm by applying the conventional Wiener filter in the spectro-temporal modulation domain. The multi-resolution spectro-temporal analysis and synthesis framework for Fourier spectrograms [12] is extended to the analysis-modification-synthesis (AMS) framework for speech enhancement. Compared with conventional speech enhancement algorithms, a Wiener filter and an extended minimum mean-square error (MMSE) algorithm, our proposed method outperforms them by a large/small margin in white/babble noise conditions from both objective and subjective evaluations.
VOICE ACTIVITY DETECTION BASED ON FREQUENCY MODULATION OF HARMONICS
(2013)
Hsu, Chung-Chien
;
Lin, Tse-En
;
Chen, Jian-Hueng
;
Chi, Tai-Shih
;
電機資訊學士班
In this paper, we propose a voice activity detection (VAD) algorithm based on spectro-temporal modulation structures of input sounds. A multi-resolution spectro-temporal analysis framework is used to inspect prominent speech structures. By comparing with an adaptive threshold, the proposed VAD distinguishes speech from non-speech based on the energy of the frequency modulation of harmonics. Compared with three standard VADs, ITU-T G. 729B, ETSI AMR1 and AMR2, our proposed VAD significantly outperforms them in non-stationary noises in terms of the receiver operating characteristic (ROC) curves and the recognition rates from a practical distributed speech recognition (DSR) system.