Predictive VQ for noisy channel spectrum coding: AR or MA?

Skoglund, Jan; Linden, J.

doi:10.1109/icassp.1997.596197

Cited by 21 publications

(12 citation statements)

References 9 publications

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“…It was observed that exploiting the interframe correlation the transparent quality is obtained at lower bit-rates, as proven by the better results of predictive VQ when compared to memoryless VQ [10]. Principal component analysis can provide another effective method of taking advantage of LSF coefficients redundancy, as shown in [13], where the Karhunen Loeve transform is applied to LSF coefficients and only 7 out of 10 of the transformed coefficients are transmitted, resulting in transparent quality at a rate of 22 bits/frame.…”

Section: Introductionmentioning

confidence: 87%

“…The prediction is based only on previous quantized vectors. The predictor may be of AR or MA type and it has been shown experimentally [10] that it is sufficient to use only the diagonal elements of the prediction matrices. The AR predictor used in this study has the form: !…”

Section: Predictive Multiple-scale Lattice Vqmentioning

confidence: 99%

“…A predictive VQ [10] scheme exploits the memory of the input vectors by computing first the predicted vector and then quantizing the prediction error. The prediction is based only on previous quantized vectors.…”

Section: Predictive Multiple-scale Lattice Vqmentioning

confidence: 99%

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Predictive multiple-scale lattice VQ for LSF quantization

Vasilache

Vasilache²,

Tăbuş³

1999

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)

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This paper introduces a new lattice quantization scheme, the multiple-scale lattice vector quantization (MSLVQ), based on the truncation of the D + 10 lattice. The codebook is composed of several copies of the truncated lattice scaled with different scaling factors. A fast nearest neighbor search is introduced. We compare the performance of predictive MSLVQ for quantization of LSF coefficients with the quantization technique used in the codec G.729 and show the better performance of our method in terms of spectral distortion. The MSLVQ scheme achieves the transparent quality at 21 bits/frame.

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Section: Introductionmentioning

confidence: 87%

Section: Predictive Multiple-scale Lattice Vqmentioning

confidence: 99%

See 1 more Smart Citation

Predictive multiple-scale lattice VQ for LSF quantization

Vasilache

Vasilache²,

Tăbuş³

1999

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258)

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show abstract

“…The CSI scheme can also benefit from the existence of the jitter buffer, and utilize the received spectral envelopes. In a way, CSI is already used in speech coding since the widely used Predictive Coding of LSFs [8] can be seen as a form of CSI: the current LSFs are encoded having the previous LSFs as side information.…”

Section: Introductionmentioning

confidence: 99%

Coding with Side Information Techniques for LSF Reconstruction in Voice Over IP

Agiomyrgiannakis

Stylianou²

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.

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In applications like VoIP, speech codecs have to deal with excessive packet losses, caused by network errors and/or delays. In this paper a new method for the reconstruction of lost speech spectral envelopes is presented, which is based on a statistical estimation function. We suggest the usage of a minimal "corrective" bitstream and propose Coding with Side Information (CSI) techniques for an efficient Forward Error Correction (FEC) strategy. The proposed methods are tested on multiple scenarios of missing frames. Objective results indicate that with only 4 bits per lost frame, a spectral distortion reduction of 0.77-1.14 dB is achieved, compared to results obtained by current state-of-the-art estimation methods. Compared to "predictive" estimation methods, the use of jitter buffer as side information and 4 bits per lost frame provide a 42% reduction of spectral distortion for single packet losses, and a 32% reduction for double packet losses. Subjective results indicate that the corrected speech has fewer artifacts.

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“…Moving Average (MA) is generally used as it limits error propagation, while the more efficient Differential Quantisation (DQ) schemes propagate them [8]. However, as a given packet contains descriptions of successive packets, it is possible to use a first order DQ to predict F m+1 from F m , and a second order DQ to predict F m+2 from F m+1 and F m .…”

Section: Parametermentioning

confidence: 99%

Multiple Description Coding for Voice over IP using Sinusoidal Speech Coding

Orozco

Villette

Kondoz

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings

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CELP coders, such as G.729, are often used in VoIP systems as they offer good speech quality in the absence of packet losses. However, their reliance on long-term prediction causes propagation of errors across speech frames, and therefore makes CELP coders more sensitive to packet losses. Sinusoidal coders on the other hand do not rely on long-term prediction, and may be a good alternative for VoIP due to their higher resilience to packet losses. In this paper a comparison is made between CELP and sinusoidal coders in a VoIP application. A packetisation scheme based on Multiple Description Coding (MDC) applied to the sinusoidal coder is presented. The results show that under typical VoIP operating conditions, the sinusoidal coder based systems can outperform CELP based systems at equal bit rate, especially for high packet loss rates.

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Predictive VQ for noisy channel spectrum coding: AR or MA?

Cited by 21 publications

References 9 publications

Predictive multiple-scale lattice VQ for LSF quantization

Predictive multiple-scale lattice VQ for LSF quantization

Coding with Side Information Techniques for LSF Reconstruction in Voice Over IP

Multiple Description Coding for Voice over IP using Sinusoidal Speech Coding

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