Tandem-STRAIGHT: A temporally stable power spectral representation for periodic signals and applications to interference-free spectrum, F0, and aperiodicity estimation

Kawahara, Hideki; Morise, Masanori; Takahashi, Tôru; Nisimura, Ryuichi; Irino, Toshio; Banno, Hideki

doi:10.1109/icassp.2008.4518514

Cited by 266 publications

(194 citation statements)

References 9 publications

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“…The instantaneous phase of a signal can be calculated by Hilbert transform as (10). Due to the fact that the valid phase scope of the operation tan -1 is 0~ , we can correct the frequency by the proposed method when f c ranges from 0.67f 0 to 2f 0 theoretically.…”

Section: A Basic Principlementioning

confidence: 99%

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A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency

Zhao¹,

Chen²,

Yun³

et al. 2014

JACN

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Abstract-The speech fundamental frequency (F0) is an important speech parameter which has significant effect in domains such as voiceprint analysis, speaker recognition, voice conversion and etc. The existing extraction methods of speech fundamental frequency are not satisfactory in terms of accuracy due to the limitations of the methods themselves and noise so that correction is essential for high-quality analysis, recognition, conversion. The effect of existing correction methods rely heavily on the accuracy of first extraction, and are sensitive to noise. This article proposes a new correction method which makes use of cross-correlation of original signal and estimated signal to convert the difference between their frequencies to phase difference, thereby gains the accurate fundamental frequency by measuring this phase difference. Experiments indicate that the proposed method is effective when the estimated frequency ranges from 70% to 190% of the actual frequency, and keeps the average error within -50dB (0.35%) when signal to noise ratio (SNR) reduces to 3dB.Index Terms-Speech fundamental frequency, precision correction, large scale, anti-noise, phase difference.

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Section: A Basic Principlementioning

confidence: 99%

“…Now lots of speech analysis/synthesis [6], [7] frameworks use fundamental frequency as an important model parameter such as STRAIGHT [8]- [10]. The STRAIGHT express speech as fundamental frequency and spectral envelope and can easily manipulate these parameters and synthetize the manipulated speech as well.…”

Section: Introductionmentioning

confidence: 99%

A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency

Zhao¹,

Chen²,

Yun³

et al. 2014

JACN

View full text Add to dashboard Cite

show abstract

“…There are other attempts to jointly model speech parameters, such as the S-TRAIGHT model [14] and the compound model [1]. Compared to these previous models, PAT2 is probabilistic and much more comprehensive, which incorporates mixed excitation, glottal wave and phase modeling.…”

Section: Related Work and Conclusionmentioning

confidence: 99%

Improvement of Probabilistic Acoustic Tube model for speech decomposition

Zhang

Hasegawa‐Johnson

2014

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

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Current model-based speech analysis tends to be incomplete -only a part of parameters of interest (e.g. only the pitch or vocal tract) are modeled, while the rest that might as well be important are disregarded. The drawback is that without joint modeling of parameters that are correlated, the analysis on speech parameters may be inaccurate or even incorrect. Under this motivation, we have proposed such a model called PAT (Probabilistic Acoustic Tube), where pitch, vocal tract and energy are jointly modeled. This paper proposes an improved version of PAT model, named PAT2, where both signal and probabilistic modeling are tremendously renovated. Compared to related works, PAT2 is much more comprehensive, which incorporates mixed excitation, glottal wave and phase modeling. Experimental results show its ability in decomposing speech into desirable parameters and its potential for speech synthesis.

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“…According to the obtained state durations, a sequence of spectral and pitch values is generated from the sentence HMM by using the speech parameter generation algorithm [14]. Finally, the STRAIGHT vocoder [15] is responsible for synthesizing a speech waveform from the generated parameters. The whole idea is depicted in Fig.…”

Section: Speech Synthesismentioning

confidence: 99%

Distributed Web Service Architecture towards Robotic Speech Communication: A Vietnamese Case Study

Pham

Dau

2013

International Journal of Advanced Robotic Systems

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Robotics is emerging as one of the most prominent research areas in the world and is recently attracting the Vietnamese research community. For the purpose of determining an entrance for a Vietnamese human interacting robotics system, this paper is aimed at proposing a service-oriented architecture for location assistance robotic systems made out of loosely-coupled and distributed web services. The proposed platform consists of two major components: a Speech Processing System (SPS) and a Service Manipulating System (SMS). This architecture allows our robot to meet three critical human interaction robotic systems requirements: flexibility, scalability and reliability.

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Tandem-STRAIGHT: A temporally stable power spectral representation for periodic signals and applications to interference-free spectrum, F0, and aperiodicity estimation

Cited by 266 publications

References 9 publications

A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency

A Precision, Large Scale, Anti-Noise Method for Correction of Speech Fundamental Frequency

Improvement of Probabilistic Acoustic Tube model for speech decomposition

Distributed Web Service Architecture towards Robotic Speech Communication: A Vietnamese Case Study

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