Code Excited Linear Prediction Research Articles

A Comparative Study of Speech Coding Techniques for Electro Larynx Speech Production

Speech coding is a method of earning a tight speech signals representation for efficient storage and efficient transmission over band limited wired or wireless channels. This is usually achieved with acceptable representation and least number of bits without depletion in the perceptual quality. A number of speech coding methods already developed and various speech coding algorithms for speech analysis and synthesis are used. This paper deals with the comparison of selected coding methods for speech signal produced by Electro Larynx (EL) device. The latter is a device used by cancer patients with their vocal laryngeal cords being removed. The used methods are Residual-Excited Linear Prediction (RELP), Code Excited Linear Prediction (CELP), Algebraic Code Excited Linear Predictive (ACELP), Phase Vocoders based on Wavelet Transform (PVWT), Channel Vocoders based on Wavelet Transform (CVWT), and Phase vocoder based on Dual-Tree Rational-Dilation Complex Wavelet Transform (PVDT-RADWT). The aim here is to select the best coding approach based on the quality of the reproduced speech. The signal used in the test is speech signal recorded either directly by normal persons or else produced by EL device. The performance of each method is evaluated using both objective and subjective listening tests. The results indicate that PVWT and ACELP coders perform better than other methods having about 40 dB SNR and 3 PESQ score for EL speech and 75 dB with 3.5 PESQ score for normal speech, respectively.

Mel Scale-Based Linear Prediction Approach to Reduce the Prediction Filter Order in CELP Paradigm

This paper proposes a novel method to reduce the order of prediction filter from 10 to 7 in Code Excited Linear Prediction (CELP) coding framework by the inclusion of psychoacoustic Mel scale into Linear Predictive Coding (Mel-LPC). Efficient quantization methods using 2-split Vector Quantization (VQ) for Mel-LPC obtained a reduction of 4 bits/frame and resulted in a total bit gain of 200 bps. A weighting scheme for the Euclidean distance measure gave a reduction of 6 bits/frame that adds up to a total bit gain of 300 bps. A lower Mel-LPC order of 3 has been employed for unvoiced frames by using the perceptual quality as selection criteria and an efficient VQ method using 5 bits is developed which brought down the average bit requirement to 11.5 bits/frame. To incorporate this into Mel-LPC-based CELP encoding scheme, a neural network-based voiced-unvoiced classification algorithm using 5 derived features as input has been constructed and this selection of filter order based on signal statistics provides the benefit of bit reduction by 625 and 325 bps, respectively, for 10th order LPC and 7th order Mel-LPC. In addition to all, the incorporation of Mel-LPC gives a better performance in the estimation of formants.

A Secure AMR Fixed Codebook Steganographic Scheme Based on Pulse Distribution Model

Adaptive multi-rate (AMR), a popular audio compression standard, is widely used in mobile communication and mobile Internet applications and has become a novel carrier for hiding information. To improve the statistical security, this paper presents a steganographic scheme in the AMR fixed codebook (FCB) domain based on the pulse distribution model (PDM-AFS), which is obtained from the distribution characteristics of the FCB value in the cover audio. The pulse positions in stego audio are controlled by message encoding and random masking to make the statistical distribution of the FCB parameters close to that of the cover audio. The experimental results show that the statistical security of the proposed scheme is better than that of the existing schemes. Furthermore, the hiding capacity is maintained compared with the existing schemes. The average hiding capacity can reach 2.06 kbps at an audio compression rate of 12.2 kbps, and the auditory concealment is good. To the best of our knowledge, this is the first secure AMR FCB steganographic scheme that improves the statistical security based on the distribution model of the cover audio. This scheme can be extended to other audio compression codecs under the principle of algebraic code excited linear prediction (ACELP), such as G.723.1 and G.729.

Low Delay Sparse and Mixed Excitation CELP Coders for Wideband Speech Coding

Code Excited Linear Prediction (CELP) algorithms are proposed for compression of speech in 8 kHz band at switched or variable bit rate and algorithmic delay not exceeding 2 msec. Two structures of Low-Delay CELP coders are analyzed: Low-delay sparse excitation and mixed excitation CELP. Sparse excitation is based on MP-MLQ and multilayer models. Mixed excitation CELP algorithm stems from the narrowband G.728 standard. As opposed to G.728 LD-CELP coder, mixed excitation codebook consists of pseudorandom vectors and sequences obtained with Long-Term Prediction (LTP). Variable rate coding consists in maximizing vector dimension while keeping the required speech quality. Good speech quality (MOS=3.9 according to PESQ algorithm) is obtained at average bit rate 33.5 kbit/sec.

Mutual Information, the Linear Prediction Model, and CELP Voice Codecs

We write the mutual information between an input speech utterance and its reconstruction by a code-excited linear prediction (CELP) codec in terms of the mutual information between the input speech and the contributions due to the short-term predictor, the adaptive codebook, and the fixed codebook. We then show that a recently introduced quantity, the log ratio of entropy powers, can be used to estimate these mutual informations in terms of bits/sample. A key result is that for many common distributions and for Gaussian autoregressive processes, the entropy powers in the ratio can be replaced by the corresponding minimum mean squared errors. We provide examples of estimating CELP codec performance using the new results and compare these to the performance of the adaptive multirate (AMR) codec and other CELP codecs. Similar to rate distortion theory, this method only needs the input source model and the appropriate distortion measure.

Transform-Domain Speech Bandwidth Extension

The limited speech bandwidth used in narrowband telephone systems degrades both the quality and the intelligibility of speech. This paper proposes a new transform-domain speech bandwidth extension method. The method uses discrete wavelet transform–fast Fourier transform-based data hiding technique to provide a better quality wideband speech signal. The code-excited linear prediction parameters of the missing speech are hidden within the narrowband speech signal. The hidden information is recovered at the receiving end to produce a wideband speech signal. Theoretical and simulation analyses show that the proposed method is robust to quantization and channel noises. Obtained results confirm the excellent reconstructed wideband speech quality of the proposed method over traditional methods.

A scalable wideband speech codec using the wavelet packet transform based on the internet low bitrate codec

Most recent speech codecs employ code excited linear prediction (CELP) and transmit side information to improve speech quality under packet loss. Another approach to achieve high robustness to packet loss is to use the frame independent coding scheme based on the internet low bitrate codec (iLBC). The scalable wideband speech codec based on the iLBC was previously presented and outperformed G.729.1 at most bit rates according to the objective quality. This paper presents improvements to the previous work. Specifically, we employ the wavelet packet transform (WPT) instead of the modified discrete cosine transform (MDCT) to enhance the quality, and evaluate the proposed codec based on both the objective and subjective quality measures. The objective quality evaluation results show that clear improvement is achieved and that the proposed codec outperforms G.729.1 at the bit rate of 18 kbps or higher under clean channel conditions and has higher robustness to packet loss than G.729.1. The informal subjective test results also show similar trends.

Speaker verification from codec distorted speech for forensic investigation through serial combination of classifiers

Forensic investigation often uses biometric evidence as important aids for identifying the culprits. Speech is one of the easily available biometrics in today's hi-tech world. But, most of the speech biometric evidence acquired for investigative purposes will usually be highly distorted. Among these distortions, most prominent is the distortion introduced by the speech codec. Speech codec may either remove or distort some of the speaker-specific features, and this may reduce the speaker verification accuracy. The effect of distortion on commonly used speaker-specific features namely Mel Frequency Cepstral Coefficients (MFCC) and Power Normalized Cepstral Coefficients (PNCC), due to Code Excited Linear Prediction (CELP) codec (the most widely used speech codec in today's mobile telephony), is quantified in this paper. The features which are least affected by the codec are experimentally determined as PNCC. But, when these PNCC coefficients are directly employed, speaker verification error rate obtained is 20% with Gaussian Mixture Model-Universal Background Model (GMM-UBM) classifier. To improve the verification accuracy, PNCCs are slightly modified, and these modified PNCCs (MPNCC) are used as the feature set for the speaker verification. With these modified PNCCs, the error rate is reduced to 15%. By fusing these MPNCCs with MFCC, the error rate is further reduced to 8.75%. A series combination of GMM-UBM and Support Vector Machine (SVM) classifiers is also proposed here to enhance the speaker verification accuracy further. The speaker verification error rates for different baseline classifiers are compared with that of the proposed serially combined GMM-UBM and SVM classifiers. The classifier fusion with the fused feature set largely reduced the error rates to 2.5% which is very much less than that of baseline classifiers with normal PNCC features. Hence, this system is a good candidate for investigative purposes.

高能率符号励振線形予測符号化と帯域選択型変形離散余弦変換符号化を用いた32kbit/sスケーラブル広帯域音声・オーディオ符号化方式の開発

高能率符号励振線形予測符号化と帯域選択型変形離散余弦変換符号化を用いた32kbit/sスケーラブル広帯域音声・オーディオ符号化方式の開発

A Search Complexity Improvement of Vector Quantization to Immittance Spectral Frequency Coefficients in AMR-WB Speech Codec

An adaptive multi-rate wideband (AMR-WB) code is a speech codec developed on the basis of an algebraic code-excited linear-prediction (ACELP) coding technique, and has a double advantage of low bit rates and high speech quality. This coding technique is widely used in modern mobile communication systems for a high speech quality in handheld devices. However, a major disadvantage is that a vector quantization (VQ) of immittance spectral frequency (ISF) coefficients occupies a significant computational load in the AMR-WB encoder. Hence, this paper presents a triangular inequality elimination (TIE) algorithm combined with a dynamic mechanism and an intersection mechanism, abbreviated as the DI-TIE algorithm, to remarkably improve the complexity of ISF coefficient quantization in the AMR-WB speech codec. Both mechanisms are designed in a way that recursively enhances the performance of the TIE algorithm. At the end of this work, this proposal is experimentally validated as a superior search algorithm relative to a conventional TIE, a multiple TIE (MTIE), and an equal-average equal-variance equal-norm nearest neighbor search (EEENNS) approach. With a full search algorithm as a benchmark for search load comparison, this work provides a search load reduction above 77%, a figure far beyond 36% in the TIE, 49% in the MTIE, and 68% in the EEENNS approach.

Low complexity forward error correction for CELP-type speech coding over erasure channel transmission

One of the well-known problems of Code-Excited Linear Prediction (CELP)-type codec is its vulnerability to a frame erasure. When a frame is erased, the inter-frame dependency introduced by the Long Term Prediction causes a desynchronization of the Adaptive Codebook (ACB) which introduces in its turn an error propagation through the correctly received frames. In this paper, we propose a media-specific Forward Error Correction (FEC) method using a Pitch-Pulse Codebook (PPCB)-based approach to model the ACB contribution for voiced frame (frame onset) determined under Zero Crossing Rate constraint. The PPCB uses a single pulse optimized by Multipulse Maximum Likelihood Quantization algorithm to model the pitch-like contribution at the encoder side while the quantized version of that pulse will be sent as FEC information to resynchronize the ACB at the decoder side after a frame erasure. Through this approach a noticeable improvement of the synthesis speech quality is achieved under adverse channel conditions with the advantage of low computational complexity while the legacy bit-rate of the codec is kept unchanged.

Residual Excited Linear Predictive Coding

Residual Excited Linear Predictive Coding

Analysis-by-synthesis compression of range-focused SAR raw data

We propose a predictive compression scheme for synthetic aperture radar (SAR) raw data based on the analysis-by-synthesis encoding method. The algorithm is inspired by the code excited linear prediction (CELP) algorithm used in speech compression and exploits the correlation across azimuth of the range-focused SAR data. We also extend this approach to include multiple codebooks and obtain the performance of the proposed methods on recorded data. Numerical results show that these algorithms outperform the open-loop predictive quantization schemes.

Speaker verification method for operation system of consumer electronic devices

A system is proposed that can remotely operate consumer electronic devices by voice. It uses the mobile phone as a controller. And it uses the CELP(code excited linear prediction) parameters that are used for speech coding in mobile phones. A speaker verification function protects private information and separates the user's voice from that of people nearby who are also speaking. A CELP-based speaker verification method is used to match the audio stream by comparing the trajectories of continuous phonemes. Experimental evaluation of the speaker verification method demonstrated the effectiveness of the proposed verification method.1.

IJARCCE - Computer and Communication Engineering

Speech compression is the technique of converting human speech into an efficiently encoded format that can later be decoded to produce a close approximation of the original signal. The merits of the compression technique are reduction in storage space, bandwidth, transmission power and energy. An efficient algorithm Discrete Wavelet Transform (DWT) is employed for decomposition of original signal into wavelets coefficients at different scales and positions and these coefficients are truncated to perform encoding and decoding. The compression technique used in this paper is better than other earlier coding techniques like μ-law coding, code excited linear predictive coding. Speech compression plays a prominent role in speech signal processing such as satellite communications, internet communications, transmission of biomedical signals and other applications.

Speech Coding Techniques

Abstract Speech coding has been major issue in the area of digital speech processing. Speech coding is the process of transforming the speech signal in a more compressed form, which can then be transmitted with few numbers of binary digits. It is not possible to access unlimited bandwidth of a channel each time we send a signal across it which leads to code and compress speech signals. Speech compression is applied in long distance communication, high-class speech storage, and message encryption. Speech coding is a lossy type of coding and hence the output signal does not exactly sound like the input. Speech coding techniques discussed here are Linear predictive coding, waveform coding, Code excited linear predictive coding, etc. Linear Predictive Coding and Code Excited Linear Predictive Coding techniques are studied with the help of MATLAB to check their performance measures like compression ratio and speech audible quality.

Algebraic codebook search strategy for an algebraic code‐excited linear‐prediction speech coder by means of reduced candidate mechanism and iteration‐free pulse replacement

This work aims to present a combined version of reduced candidate mechanism (RCM) and iteration-free pulse replacement (IFPR) as a novel and efficient way to enhance the performance of algebraic codebook search in an algebraic code-excited linear-prediction speech coder. As the first step, individual pulse contribution in each track is given by RCM, and the value of N is then specified. Subsequently, the replacement of a pulse is performed through the search over the sorted top N pulses by IFPR, and those of 2–4 pulses are carried out by a standard IFPR. Implemented on a G.729A speech codec, this proposal requires as few as 20 searches, a search load tantamount to 6.25% of G.729A, 31.25% of the global pulse replacement method (iteration = 2), 41.67% of IFPR, but still provides a comparable speech quality in any case. The aim of significant search performance improvement is hence achieved in this work.

IJARCCE - Computer and Communication Engineering

In wireless communication system, limited bandwidth and power is the primary restriction. The existing wireless systems involved in transmission of speech visualized that efficient and effective methods be developed to transmit and receive the same while maintaining quality of speech, especially at the receiving end. Speech coding technique is a material of research for the scientific and academic community since the era of digitization (digital). Amongst all elements of the communication systems (transmitter, channel and receiver), transmission channel is the most critical and plays a key role in the transmission and reception of information. The quality of speech at receiver end decides by channel conditions. Modelling a channel is a multifarious task. A number of techniques are adopted to alleviate the effect of the channel. Adaptive Multi Rate is one of the techniques that neutralize the deleterious effect of the channel on speech. This technique utilizes variable bit rate that dynamically switches to specific modes of operation depending upon the channel conditions. For example, Low bit rate mode of operation is selected in adverse channel conditions, this helps to provide more error protection bits for channel coding and vice versa. Therefore, in this paper, application of Code Excited Linear Prediction (CELP) source codec on speech followed by AMR codec is studied. Further, higher the bit rate used, the better is the quality of speech. In this paper apart from speech codec about AMR is also studied that why the AMR is proposed for the GSM, how the bits rates are reduced in AMR, operation of AMR and other applications of AMR.

Speech Coding Based on Compressed Sensing and Sparse Representation

In this paper, we propose a novel speech coding scheme based on compressed sensing and sparse representation. Compressed sensing (CS) attracts great interest for its ability to utilize a few measurements to recover original signals. Measurements preserve part of speech features while projected by row echelon matrix. A dictionary is learned in order to contain redundant information about speech measurements. The synthesized speech is recovered from a sparse approximation of the corresponding measurement. A rear low-pass filter is adopted to improve the subject quality of synthesized speech. Results show that the proposed coding scheme has achieved average Mean Opinion Score (MOS) of the synthesized speech 3.083 in an appropriate bit rate (4.2 Kbps), which outperforms the quality of Code excited linear prediction (CELP).

An efficient algebraic codebook search for ACELP speech coder

Abstract In a bid to enhance the search performance, this paper presents an improved version of reduced candidate mechanism (RCM), an algebraic codebook search conducted on an algebraic code-excited linear prediction (ACELP) speech coder. This improvement is made based on two findings in a piece of our prior work. The first finding is that a pulse with a high contribution in the associated track is more likely to serve as an optimal pulse in the optimal codevector and the second is that the speech quality can be well maintained at a search accuracy above 50% approximately. Subsequently, a new finding in this study concerning a structured algebraic codebook in G.729 indicates that there is a 0.8321 probability that the number 1 ranked pulse in a global sorting by pulse contribution is indeed one of the optimal pulses. Hence, the number 1 pulse in the global sorting is labeled as one of the optimal pulses, following which a sequence of search tasks are fulfilled through RCM. This proposed complexity reduction algorithm, implemented on a G.729A speech codec, takes as few as eight searches, a search load tantamount to 2.5% of G.729A, 12.5% of global pulse replacement method (iteration = 2), 16.7% of iteration-free pulse replacement method, and 50% of RCM (N = 2). This proposal is thus found to successfully reduce the required computational complexity to a great extent as intended.