• 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.

• Journal of IKEEE
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• v.24 no.4
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• pp.1122-1128
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• 2020

Bandwidth Extension refers to restoring and expanding a narrow band signal(NB) that is damaged or damaged in the encoding and decoding process due to the lack of channel capacity or the characteristics of the codec installed in the mobile communication device. It means converting to a wideband signal(WB). Bandwidth extension research mainly focuses on voice signals and converts high bands into frequency domains, such as SBR (Spectral Band Replication) and IGF (Intelligent Gap Filling), and restores disappeared or damaged high bands based on complex feature extraction processes. In this paper, we propose a model that outputs an bandwidth extended signal based on an autoencoder among deep learning models, using the residual connection of one-dimensional convolutional neural networks (CNN), the bandwidth is extended by inputting a time domain signal of a certain length without complicated pre-processing. In addition, it was confirmed that the damaged high band can be restored even by training on a dataset containing various types of sound sources including music that is not limited to the speech.

• MALSORI
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• no.52
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• pp.133-144
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• 2004

The quality of narrowband speech can be enhanced by the bandwidth extension technology. This paper proposes a mixed excitation and an energy compensation method based on Gaussian Mixture Model (GMM). First, we employ the mixed excitation model having both periodic and aperiodic characteristics in frequency domain. We use a filter bank to extract the periodicity features from the filtered signals and model them based on GMM to estimate the mixed excitation. Second, we separate the acoustic space into the voiced and unvoiced parts of speech to compensate for the energy difference between narrowband speech and reconstructed highband, or lowband speech, more accurately. Objective and subjective evaluations show that the quality of wideband speech reconstructed by the proposed method is superior to that by the conventional bandwidth extension method.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1760-1770
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• 2018

This paper presents a control bandwidth extension method for inverters with a low carrier ratio. The bandwidth is extended at the price of decreasing the phase margin. Then the phase margin is compensated by introducing an extra leading angle into an inverse Park transformation. The model of the controller with the proposed method is established. The magnitude and phase characteristics are also analyzed. Then the influence on system stability when the leading angle is introduced is analyzed. The proposed method is applied to design an inverter controller with both a large bandwidth and a desired phase margin, and the experimental results verify that the controller performs well in the steady-state and in terms of transient response.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.175-178
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• 2002

Most existing telephone networks transmit narrowband speech witch has been bandlimited below 4 kHz. Compared with wideband speech up to 8 kHz, narrowband speech shows reduced intelligibility and a muffled quality. Bandwidth extension is a technique to generate wideband speech by reconstructing 4-8 kHz highband speech without any additional information. This paper presents experimental results of the bandwidth extension adopted for 4800 bps CELP speech coder. In this experiment, we examine various methods for reconstruction of wideband spectrum and excitation signal, compare and analyze their performance by performing the subjective preference test and measuring the cepstral distortion.

• 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.

• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.1-8
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• 2003

Scheduling technology is one of the most important elements required to support the Quality of service (QoS) in the Internet and a lot of scheduling algorithms have been developed. However, most of these algorithms ire not flexible to distribute the excess bandwidth. In order to provide flexibility for distributing the excess bandwidth, we proposed excess bandwidth fair queueing (EBFQ) algorithm with relatively low complexity. In this paper, we propose the new extension to this EBFQ algorithm for the hierarchical fair queueing system. This extension can be naturally applied to the existing hierarchical algorithm and simultaneously provide the same level of fairness. Through the simulation and analysis, we verify it.

• 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.3
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• pp.119-128
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• 2008

This paper analyzes the relationship between two representative statistical methods for bandwidth extension (BWE): Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) ones, and compares their performances. The HMM method is a memory-based system which was developed to take advantage of the inter-frame dependency of speech signals. Therefore, it could be expected to estimate better the transitional information of the original spectra from frame to frame. To verify it, a dynamic measure that is an approximation of the 1st-order derivative of spectral function over time was introduced in addition to a static measure. The comparison result shows that the two methods are similar in the static measure, while, in the dynamic measure, the HMM method outperforms explicitly the GMM one. Moreover, this difference increases in proportion to the number of states of HMM model. This indicates that the HMM method would be more appropriate at least for the 'blind BWE' problem. On the other hand, nevertheless, the GMM method could be treated as a preferable alternative of the HMM one in some applications where the static performance and algorithm complexity are critical.