• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.197-204
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• 2013

In this paper, we propose a new method for artificial bandwidth extension of narrow-band signal in frequency domain. In the proposed method, a narrow-band signal is decomposed into excitation signal and spectral envelope, which are extended independently in frequency domain. The excitation signal is extended such that low-band harmonic structure is maintained in high band, and the spectral envelope is extended based on sub-band energy using NMF. Finally, the spectral phase is determined based on signal correlation between frames in time domain, resulting in the final wide-band signal. The subjective evaluation verified that the wide-band signal generated by the proposed method has a higher quality than the original narrow-band signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.431-433
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• 2018

This paper proposes the system that offer super-wideband speech which is made by artificial bandwidth extension technique using wideband speech signal in time-domain. wideband excitation signal and line spectrum pair(LSP) are extracted based on source-filter model in time-domain. Two parameters are extended by each bandwidth extension algorithms, and then, super-wideband speech parameters are estimated. and synthesized. Subjective test shows super-wideband speech is better speech quality than wideband speech signal.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.70-77
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• 2017

Bandwidth extension is a technique to improve speech quality, intelligibility and naturalness, extending from the 300 ~ 3,400 Hz narrowband speech to the 50 ~ 7,000 Hz wideband speech. In this paper, an Artificial Bandwidth Extension (ABE) module embedded in the Opus audio decoder is designed using the information of narrowband speech to reduce the computational complexity of LPC (Linear Prediction Coding) and LSF (Line Spectral Frequencies) analysis and the algorithm delay of the ABE module. We proposed a spectral envelope extension method using DBN (Deep Belief Network), one of deep learning techniques, and the proposed scheme produces better extended spectrum than the traditional codebook mapping method.

• The Journal of the Acoustical Society of Korea
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• v.30 no.4
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• pp.190-196
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• 2011

Bandwidth extension is a technique to improve speech quality and intelligibility, extending from 300-3400 Hz narrowband speech to 50-7000 Hz wideband speech. This paper designs an artificial bandwidth extension (ABE) module embedded in the AMR (adaptive multi-rate) decoder, reducing LPC/LSP analysis and algorithm delay of the ABE module. We also introduce a fast search codebook mapping method for ABE, and design a low power BWE technique based on the AMR decoder. The proposed ABE method reduces the computational complexity and the algorithm delay, respectively, by 28 % and 20 msec, compared to the traditional DTE (decode then extend) method. We also introduce a weighted classified codebook mapping method for constructing the spectral envelope of the wideband speech signal.

• The Journal of the Acoustical Society of Korea
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• v.27 no.6
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• pp.309-318
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• 2008

In this paper, we discuss a method for efficiently coding the high-band signal in the split-band coding approach where an input signal is divided into two bands and then each band may be encoded separately. Generally, and especially through the research on the artificial bandwidth extension (BWE), it is well known that there is a correlation between the two bands to some degree. Therefore, some coding gain could be achieved by utilizing the correlation. In the BWE-prediction-based coding approach, using a simple linear BWE function may not yield optimal results because the correlation has a non-linear characteristic. In this paper, we investigate the new coding scheme more in details. A few representative BWE functions including linear and non-linear ones are investigated and compared to find a suitable one for the coding purpose. In addition, it is also discussed whether there are some additional gains in combining the BWE coder with the predictive vector quantizer which exploits the temporal correlation.