Fine granularity scalable speech coding using embedded tree-structured vector quantization

Djamah, Mouloud; O’Shaughnessy, D.

doi:10.1016/j.specom.2011.06.002

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…The PESQ scores range from 2.04 to 4.02 with an average rate of 0.12 per bit. A part of this work has been reported in [9]. Note that the tree structure allows achieving an efficient fast search algorithm at the encoding side [10].…”

Section: Performance Evaluationmentioning

confidence: 99%

An efficient tree-structured codebook design for embedded vector quantization

Djamah

O’Shaughnessy

2010

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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This paper proposes an efficient codebook design for treestructured vector quantization (TSVQ), which is embedded in nature. We modify two speech coding standards by replacing their original quantizers for line spectral frequencies (LSF's) and or Fourier magnitudes quantization with TSVQ-based quantizers. The modified coders are fine-granular bit-rate scalable with gradual change in quality for the synthetic speech.

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Section: Performance Evaluationmentioning

confidence: 99%

An efficient tree-structured codebook design for embedded vector quantization

Djamah

O’Shaughnessy

2010

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

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“…The current H.264/AVC [10] divides the video data into three levels by encoded film to distinguish the importance. Scalable coding, such as fine scalable coding and progressive fine granularity scalable coding divide coding data into the base layer and enhancement layer [11][12], and subsequent enhancement layer must rely on the basic layer data decoding. So it is considered that the importance of basic layer is higher than the subsequent enhancement one.…”

Section: Introductionmentioning

confidence: 99%

An Important Frame Distinction Model of Stereoscopic Video Based on Content

Wang

et al. 2014

JMM

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As different frame lost will lead to different distortion for stereoscopic video sequence, we take into account the temporal and spatial correlation of stereo video, error diffusion characteristics left and of right view frame, as well as recursion theory. Based on the above, we put forward a frame important distinction model of stereoscopic video based on content. The experimental results show that the model can be applied for stereoscopic video sequences with different motion intensity and disparity, accordingly, code ends can accurately estimate the importance of each frame for terminal perception. Finally, the applicability of the model is discussed.

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“…Thus, the ability of VQ to balance storage and computational complexity is useful in handheld device applications that involve multimedia data. VQ then could be applied to different applications such as 3D medical image compression [6], speech coding [7], information hiding [8,9], and artistic style learning [10].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

Chen

2014

Mathematical Problems in Engineering

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Multimedia data is a popular communication medium, but requires substantial storage space and network bandwidth. Vector quantization (VQ) is suitable for multimedia data applications because of its simple architecture, fast decoding ability, and high compression rate. Full-search VQ can typically be used to determine optimal codewords, but requires considerable computational time and resources. In this study, a hybrid VQ combining a tree structure and a Voronoi diagram is proposed to improve VQ efficiency. To efficiently reduce the search space, a tree structure integrated with principal component analysis is proposed, to rapidly determine an initial codeword in low-dimensional space. To increase accuracy, a Voronoi diagram is applied to precisely enlarge the search space by modeling relations between each codeword. This enables an optimal codeword to be efficiently identified by rippling an optimal neighbor from parts of neighboring Voronoi regions. The experimental results demonstrated that the proposed approach improved VQ performance, outperforming other approaches. The proposed approach also satisfies the requirements of handheld device application, namely, the use of limited memory and network bandwidth, when a suitable number of dimensions in principal component analysis is selected.

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Fine granularity scalable speech coding using embedded tree-structured vector quantization

Cited by 3 publications

References 34 publications

An efficient tree-structured codebook design for embedded vector quantization

An efficient tree-structured codebook design for embedded vector quantization

An Important Frame Distinction Model of Stereoscopic Video Based on Content

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

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