A Low Bit Rate Audio Bandwidth Extension Method for Mobile Communication

Hang, Bo; Hu, Ruimin; Li, Xing; Fang, Yuan; Tsai, An-Chao

doi:10.1007/978-3-540-89796-5_80

Cited by 6 publications

(5 citation statements)

References 2 publications

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“…We have proposed a bandwidth extension method combines the advantages of both "blind" bandwidth extension technology and "non-blind" bandwidth extension technology [10]. However, the method can not work for music signal as well as for speech signal.…”

Section: Proposed Low Bit Rate Methodsmentioning

confidence: 99%

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Bandwidth Extension Method Based on Spectral Envelope Estimation

Hang¹,

Hu²,

Dong³

et al. 2011

JMM

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In current communication system, high quality audio signal is supposed to be provided with low bit rate and low computational complexity. This paper proposed a novel audio coding bandwidth extension method, which can improve decoded audio quality with increasing only a few coding bits per frame and a little computational complexity. This method calculate high-frequency synthesis filter by using codebook mapping method, and transmit only quantified gain corrections in high-frequency part of multiplexing coding bit stream. The preliminary test show that this method can provide comparable audio quality with lower bit consumption and computational complexity compared to the high frequency regeneration of AMR-WB+

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Section: Proposed Low Bit Rate Methodsmentioning

confidence: 99%

“…The log spectral distortion is measured: A relation between the log spectral distortion and the error of estimated parameters was formulated in [10]:…”

Section: Relationship Between Lowband and Highbandmentioning

confidence: 99%

Bandwidth Extension Method Based on Spectral Envelope Estimation

Hang¹,

Hu²,

Dong³

et al. 2011

JMM

Self Cite

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“…China AVS (Audio Video coding Standard) organization has drafted AVS-P10 (Part 10), with China's own independent intellectual property [16]. We were actively involved in the work for AVS audio coding standards, and made important contributions [17][18][19][20][21][22][23][24]. Compared with AMR-WB+, AVS-P10 achieves almost equivalent sound quality at same bitrate, so we use the audio compression algorithm in AVS-P10 to compress the virtual conference audio in the proposed system.…”

Section: B Audio Coding Algorithmmentioning

confidence: 99%

Virtual Conference Audio Reconstruction Based on Spatial Object

Hang¹,

Hu²,

Ma³

2010

JMM

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This paper proposed a virtual conference audio reconstruction model based on spatial audio object. The aim of the model is to enhance the realistic experience of virtual conference. Firstly, the conference audio synthesis method is given according the principle of the virtual conference. Then the spatial audio parameters interaural level difference (ILD) are used to reconstruct the spatial sound field for each listener based on the theory of spatial audio object coding.

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“…A small number of parameters of HF, as parametric representations of spectral envelope, are transmitted to the decoder side, such Liner Prediction Cepstral Coefficients (LPCCs), Cepstral Coefficients (CEPs), Mel Frequency Cepstral Coefficients (MFCCs), and Line Spectral Frequencies (LSFs) . In order to improve the perception quality of coding, a codebook mapping technique is also introduced for achieving more accuracy presentations of HF envelope …”

Section: Introductionmentioning

confidence: 99%

“…22 In order to improve the perception quality of coding, a codebook mapping technique is also introduced for achieving more accuracy presentations of HF envelope. 23,24 As the basic principle of the LPC-based BWE is based on the speech generation model, this approach is widely used in speech coding. [8][9][10]24 However, because the lower frequencies of voiced speech signals generally exhibit a stronger harmonic structure than the higher frequencies, the duplication of LF excitation should cause too much harmonic components on the generated HF excitation signals, which should bring out the objectionable, "buzzy"-sounding artifacts.…”

Section: Introductionmentioning

confidence: 99%

A new source‐filter model audio bandwidth extension using high frequency perception feature for IoT communications

Jiang

Wang

et al. 2018

Concurrency and Computation

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Summary Audio coding is a generic technology to IoT applications system. Audio bandwidth extension is a standard technique within contemporary audio codecs to efficiently code audio signals at low bitrates. In existing methods, high frequency signal is generated by a duplication of the corresponding low frequency and some parameters of high frequency. However, the perception quality of coding will significantly degrade if the correlation between high and low frequency becomes weak. In this paper, we proposed a new source‐filter model audio bandwidth extension method. In our method, a perception feature of the high frequency signal is extracted to restore the perception quality of coding. In the decoder side, the crest factor and noise level are obtained under the constraint of the high frequency perception parameter. The performance shown in our experiment results are superior to the classic methods. Compared with the state of art method, the proposed method is also comparative because of the coding bitrate is significantly reduced and keeps a close perception quality of coding. This paper also provided a new solution for IoT communications that requires low bitrates and high quality of coding, especially like Internet of Vehicles.

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A Low Bit Rate Audio Bandwidth Extension Method for Mobile Communication

Cited by 6 publications

References 2 publications

Bandwidth Extension Method Based on Spectral Envelope Estimation

Bandwidth Extension Method Based on Spectral Envelope Estimation

Virtual Conference Audio Reconstruction Based on Spatial Object

A new source‐filter model audio bandwidth extension using high frequency perception feature for IoT communications

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