Line Spectrum Pair Parameters Research Articles

Fast Adaptive Reconstruction Algorithm for Line Spectrum Pair Parameters Based on Compressed Sensing

Line Spectrum Pair Parameters (LSF) are important parameters in low rate speech coding. Implementing LSF transparent quantization with as few bits as possible is a research hotspot in the field of low-rate speech coding. Based on the theory of compressed sensing, this paper proposes a new adaptive reconstruction algorithm. At the encoding end, the algorithm performs frame type discrimination on the LSF of single frame or superframe after voice activation detection and then applies the compressed sensing method to observe and quantize the LSF parameters of the single frame or superframe. At the decoding end, parameters are adaptively selected according to every single frame or superframe type, so that the number of bits required to reconstruct the LSF is reduced. The experimental results show that the proposed algorithm can reduce the number of bits required for LSF reconstruction and improve the reconstruction quality under the appropriate codebook storage and search complexity.

METHOD AND APPARATUS FOR RECOVERING LINE SPECTRUM PAIR PARAMETER AND SPEECH DECODING APPARATUS USING SAME

A method and an apparatus for recovering a line spectrum pair (LSP) parameter of a spectrum region when frame loss occurs during speech decoding and a speech decoding apparatus adopting the same are provided. The method of recovering an LSP parameter in speech decoding includes: if it is determined that a received speech packet has an erased frame, converting an LSP parameter of a previous good frame (PGF) of the erased frame or LSP parameters of the PGF and a next good frame (NGF) of the erased frame into a spectrum region and obtaining a spectrum envelope of the PGF or spectrum envelopes of the PGF and NGF; recovering a spectrum envelope of the erased frame using the spectrum envelope of the PGF or the spectrum envelopes of the PGF and NGF; and converting the recovered spectrum envelope of the erased frame into an LSP parameter of the erased frame. The method and apparatus can improve the quality of a recovered speech signal, be applied to a variety of technologies, and provide a method of recovering an LSP parameter for development of an algorithm for speech decoding.

Intraframe quantization of speech line spectrum pairs for code-excited linear prediction based coders in packet networks

This paper proposes intraframe quantization schemes of line spectrum pair parameters to improve frame erasures for the ITU-T G.723.1 coder. The standard ITU-T G.723.1 coder uses an interframe quantization of the line spectrum pair parameters, which causes error propagation to the next frames. Simulation results show that our intraframe quantization schemes coding is much more robust to frame erasures than the embedded method in ITU-T G.723.1, and a typical improvement of 0.4 dB on average spectral distortion can be obtained with 40% packet loss. Enhanced modified bark spectral distortion tests, under various packet loss conditions, confirm that our proposed method is superior to the interframe algorithm embedded in the ITU-T G.723.1 coder of over 1.6. Copyright © 2012 John Wiley & Sons, Ltd.

Statistical properties of line spectrum pairs

An original method for computing the Probability Density Function (PDF) of the Line Spectrum Pair (LSP) coefficient vector as a function of the PDF of the AutoRegressive (AR) parameter vector is derived. Being linked by non-linear relations, AR parameters and LSP coefficients cannot both be Gaussian. This strict theoretical result could hide an approximately Gaussian distribution for the LSP parameters. Some distances between the LSP parameter PDF and its asymptotic Gaussian PDF are then studied. In a pattern recognition application, the LSP parameter statistics allow us to study the convexity of LSP point clusters, conditioned to each class: the LSP parameters seem to be attractive for pattern recognition when used with the centroid distance rule.

An 8-kb/s conjugate structure CELP (CS-CELP) speech coder

This paper describes a high-quality 8-kb/s speech coder called conjugate structure code-excited linear prediction (CS-CELP) with a 10-ms frame length. To provide a short delay and high quality under both error-free and channel error conditions, it uses three new schemes: line spectrum pair (LSP) quantization using interframe prediction, preselection in the codebook search, and gain vector quantization (VQ) with backward prediction. The LSP parameters are quantized by using multistage VQ with moving-average (MA) prediction. This scheme can operate efficiently with various frequency responses of speech. The preselection of the codebook reduces the computational complexity and improves the robustness to channel errors. The gain VQ with backward prediction can provide a high quality and robustness without transmission of input speech power information. A conjugate structure for both random codebook and gain codebook is introduced to improve the ability to handle random bit errors and to reduce codebook storage memory requirements. Subjective testing indicates that the quality of this coder is equivalent to that of 32-kb/s adaptive differential pulse code modulation (ADPCM) under error-free conditions. Testing has further demonstrated that the coder is robust against random bit errors.

Transparent quantization of speech LSP parameters based on KLT and 2-D-prediction

Abstruct- In this correspondence, a two-stage approach based on Karhunen-Loeve transform and 2-D prediction is proposed for efficient quantization of line spectrum pair (LSP) parameters of speech. Besides, a switched classifier is incorporated with this approach to reduce the outlier frames (spectral distortion greater than 2 dB) down to about 0.27% and to eliminate frames with spectral distortion greater than 4 dB at an average bit-rate below 19 b/frame.

Optimal transform coding for speech line spectrum pair parameters based on spectral-weighted error criterion

The line spectrum pair (LSP) is one of the most popular and efficient parameters for representing the short-time spectrum of speech signal. About 34 bits/frame is needed for direct scalar quantization of LSP parameters to maintain a good quality. Based on the spectral-weighted Euclidean distance of LSP parameters, a modified transform coding of LSP parameters which takes advantage of both strong interframe and intraframe correlations is proposed in this paper. This method incorporated with the DPCM scheme does not introduce further buffering delay. It utilizes the spectral-weighted LSP parameters in transform coding instead of LSP vector itself and needs only to quantize the prediction residuals in transformed domain. The much smaller dynamic ranges and symmetrically bell-shaped distributions of those residuals explain the success of this scheme. With the frame period of 10 ms, the spectral distortion limen of 1 dB2 can be reached at 18 bits/frame with inside training test data and 19 bits/frame with outside training test data.

Enumeration and trellis-searched coding schemes for speech LSP parameters

Speech coders employing forward adaptive predictive coding (APC) and operating at medium-to-low bit rates necessitate efficient encoding of the linear predictive coding (LPC) coefficients. Line spectrum pair (LSP) parameters are currently one of the most efficient choices of transmission parameters for the LPC coefficients. The authors briefly reviews LSP parameters and presents several low-delay coding schemes for the parameters. The coders are simulated using data generated from both the autocorrelation and covariance LPC analysis methods. The performances of the coders are given for a variety of rates and LPC analysis conditions. The most efficient scheme developed uses a uses a predictive form of trellis-coded quantization (TCQ). Its performance is comparable or superior to that of other low-delay LSP coding schemes. An enumeration scheme that reduces the rate of a given scalar quantization structure without decreasing coder performance is also presented. >

Pattern matching vocoder using LSP parameters

The system utilizes a linear predictive coding (LPC) analyzer, an Attenuator, a line spectrum pair (LSP) analyzer, a reference pattern memory and a pattern matching device. The LPC analyzer derives LPC parameters from an input speech signal. The LPC parameters are attenuated in the attenuator and fed to the LSP analyzer for deriving LSP parameters which are in turn fed to the pattern matching device. The reference pattern memory stores a plurality of reference patterns composed of a sequence of LSP parameters for a variety of predetermined speech samples. The pattern matching device is connected to the LSP analyzer and the reference pattern memory to select the reference pattern which most closely resembles the input pattern from the LSP analyzer and to provide a label code as an output thereof. On the decoding side, a decoder is responsive to the label for generating LPC parameters corresponding to the reference pattern of the label. A residual signal which is also transmitted with the reference label is received and fed with the generated LPC parameters to a synthesis filter for providing a synthesized speech signal which is subsequently converted into an analog signal.

New LSP encoding method based on two-dimensional linear prediction

A new line spectrum pair (LSP) encoding method, two-dimensional differential LSP (2DdLSP) coding, is proposed. This 2DdLSP approach simultaneously takes advantage of strong interframe and intraframe correlation of LSP parameters. The parameters to be quantised are the prediction residuals which possess the property of smaller variance than LSP parameters. This is the key point for the success of the 2DdLSP method. Three quantisation schemes, a scalar quantisation and two vector quantisations (VQs), are presented. The best result in simulation is achieved by using the product codebook VQ. A spectral distortion of 1 dB2 at 19 bits per frame can be obtained when the frame period is 10 ms. Both within-training and out-of-training tests have demonstrated the robustness of the proposed method to data variation.

A perception‐based LSP distance measure for speech recognition

Because of their high correlation and reduced sensitivity to quantization errors, the line spectrum pair (LSP) frequency parameters have been used recently for efficient quantization of LPC information for speech coding. In the present paper, the LSP representation is used for speech recognition and a new perception‐based LSP distance measure is proposed. This distance measure exploits the following two properties of the speech perception process [D. H. Klatt, Proc. ICASSP, 1278–1281 (1982)]: (1) The formant frequencies are the most important parameters for speech perception: and (2) the formant bandwidths and spectral tilt contribute very little to speech perception. The present distance measure uses these two properties in the form of weights in a weighted Euclidean distance measure. In order to derive these weights, the LPC power spectrum P(f) is computed for each speech frame and the weight for a given LSP frequency ft is taken to be proportional to [P(ft)]c. The perception‐based LSP distance measure is studied here on a speaker‐dependent speech recognition task. The optimum value of the exponent c is found here to be 0.15. The perception‐based LSP distance measure results in a recognition score of 95.7%, while the recognition accuracy is found to be 89.9% by using the conventional Euclidean distance measure on LSP parameters and 94.1% by using the liftered cepstral distance measure [B. H. Juang et al., IEEE Trans. Acoust. Speech Signal Process. ASSP‐35, 947–954 (1987)].