Speech Coding Research Articles

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.

Analytical Model for Estimating the Bounds in Predictive Entropy Coding of Digital Speech Signals

A detailed analysis of estimating the upper bounds in predictive entropy coding of digital speech signal is carried out in this paper. Lossless speech compression is exploited to measure the useful information content of the data. The bit rate achieved by the reversible compression takes into account both the contribution of the observation noise i.e. information regarding to statistical uncertainty, which is not relevant to the user, and the intrinsic information of hypothetically noise-free speech. An entropy model of the speech source is defined in order to estimate the upper bound on SQNR gain in entropy coding of digital speech signals. The gain is calculated for speech predictive coding system with non-adaptive quantizer for white and correlated noise, respectively.

Oscillatory "temporal sampling" and developmental dyslexia: toward an over-arching theoretical framework.

Oscillatory "temporal sampling" and developmental dyslexia: toward an over-arching theoretical framework.

LSP (Line Spectrum Pair): Essential Technology for High-compression Speech Coding

LSP (Line Spectrum Pair): Essential Technology for High-compression Speech Coding

Performance Analysis of Advanced Hybrid Speech Coding Techniques in Time domain, Spectral domain and Perceptual domain

Speech coding is the art of creating a minimally redundant representation of the speech signal that can be efficiently transmitted or stored in digital media and decoding the signal with the best possible perceptual Quality. The speech transmission in wireless networks is associated with the reduction of extra information present in signal in such a way to preserve the quality and intelligibility of speech. It is known that the lower the bit rate the lesser the quality of the reconstructed speech however there is a constant quest to achieve a better speech quality at lower bit-rates.This paper presents performance analysis for the quality of advanced hybrid speech coding techniques in Time domain, Spectral domain and perceptual domain. These analyses are implemented on three different algorithms of advanced hybrid speech coding techniques such as CELP, G729 Annex A, G723.1 to assess the quality performance for English female speaker, English male speaker and Arabic female speaker by using Mat lab simulation program. Our evaluation criterion implemented includes the following tests: Signal to Noise Ratio (SNR), Segmental Signal to Noise Ratio (SNRseg), The Log-Likelihood Ratio (LLR), The Weighted Spectral Slope (WSS), Absolute Error,Perceptual Evaluation of Speech Quality (PESQ),NONE">Rating of speechdistortion, rating of background noise and the predicted rating of overall quality.

An efficient search algorithm for ACELP algebraic codebook

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 on the basis of two findings in our prior work. The first finding is that a pulse with a high contribution in the associated track is more likely to serve as the optimal pulse in the optimal codevector; 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 is that there is a 0.8321 probability that the No. 1 ranked pulse in a global sorting by pulse contribution is indeed one of the optimal pulses. Hence, the No. 1 pulse in the global sorting is labeled as one of the optimal pulses, following which a sequence of search tasks is fulfilled through RCM. This proposed complexity reduction algorithm, implemented on a G.729A speech codec, takes as few as eight searches, a search load amounting 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. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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).

The Neural Substrates of Infant Speech Perception

Infants often pay special attention to speech sounds, and they appear to detect key features of these sounds. To investigate the neural foundation of speech perception in infants, we measured cortical activation using near‐infrared spectroscopy. We presented the following three types of auditory stimuli while 3‐month‐old infants watched a silent movie: (1) normal speech sounds; (2) sine wave speech (SWS) sounds consisting of three sine waves that tracked the first, second, and third formants of speech sounds; and (3) synthesized tones composed of three pure tones. Statistical analyses of oxygenated hemoglobin (oxy‐Hb) signals revealed significant activation in the left and right auditory areas in all conditions. Direct comparisons of oxy‐Hb signal changes between SWS and synthesized tones showed significant differences in the left frontal and temporal regions. Furthermore, comparisons of oxy‐Hb signal changes between speech sounds and SWS exhibited significant differences in a left posterior temporal region. These results demonstrated that functional differentiation occurs in the left temporal cortex while infants perceive different types of auditory information. Coactivation of the left temporal and frontal regions by speech sounds suggests the initial formation of a left fronto‐temporal network related to infant speech processing. Clarification of the functional role of this left‐lateralized network will help understand the speech code.

A novel approach for artificial bandwidth extension of speech signals by LPC technique over proposed GSM FR NB coder using high band feature extraction and various extension of excitation methods

This research addresses an issue of wide band (WB) speech transmission (having cut-off frequency $$\hbox {f}_{\mathrm{c}}=8$$fc=8 kHz) over standard narrow band (NB) communication link (supporting bandwidth of 300---3,400 Hz). A long transition time for technological up-gradation from NB to WB systems eventually lead to development of backward compatible techniques such as artificial bandwidth extension (ABE) which is capable of providing bandwidth of 50---7,000 Hz, in turn contributing toll quality recovered speech at receiving end. This paper investigates a novel approach to compute high band (HB) features using linear predictive coding (LPC) technique at transmitter from given input WB speech corpus. These encoded features are embedded into bitstream of proposed GSM Full Rate 06.10 NB speech coder using joint source coding and data hiding technique and then transmitted to receiver. At receiver, these HB features are extracted to reproduce HB recovered speech using watermark extraction algorithm and for the same different extension of excitation techniques have been adopted and implemented. An e-test bench is created to implement this proposed ABE coder in MATLAB and series of simulations are carried out using Subjective (mean opinion score--MOS) and Objective (perceptual evaluation of speech quality--PESQ) analysis. Obtained results for both analyses advocate performance improvement of proposed ABE coder over legacy GSM 06.10 FR NB coder for various extension of excitation techniques.

Auditory Model Identification Using REVCOR Method

Auditory models are very useful in many applications such as speech coding and compression, cochlea prosthesis, and audio watermarking. In this paper we will develop a new auditory model based on the REVCOR method. This technique is based on the estimation of the impulse response of a suitable filter characterizing the auditory neuron and the cochlea. The first step of our study is focused on the development of a mathematical model based on the gammachirp system. This model is then programmed, implemented and simulated under Matlab. The obtained results are compared with the experimental values (REVCOR experiments) for the validation and a better optimization of the model parameters. Two objective criteria are used in order to optimize the audio model estimation which are the SNR (signal to noise ratio) and the MQE (mean quadratic error). The simulation results demonstrated that for the auditory model, only a reduced number of channels are excited (from 3 to 6). This result is very interesting for auditory implants because only significant channels will be stimulated. Besides, this simplifies the electronic implementation and medical intervention.

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.

The Voice Activity Detection Algorithm Based on Spectral Entropy and High-Order Statistics

The voice activity detection is one of the key technologies of variable rate speech coding. The development of speech coding technology requires higher performance of the detection. Based on the analysis of spectral entropy and high-order statistics of the basic definition and property of the foundation, this article proposes a voice activity detection algorithm which combines spectral entropy with high-order statistics. The algorithm can effectively detect the speech and non-speech segments, and can get reasonable results in a complex background noise environment.

A nonuniform sampling technique based on inflection point detection and its application to speech coding.

In order to reduce the data amount, the nonuniform sampling (NUS) method detects samples of a signal, such as local maxima and minima. To overcome the sparseness problem of the NUS method, an inflection point detection (IPD) method is proposed to sample a signal nonuniformly. The IPD samples a signal not only at the local maxima and minima, but also at the inflection points where the slope of the signal changes. To show its usefulness, the IPD is applied to speech coding. The encoder transmits the time instants and sample amplitude values of the inflection points. At the receiver, the decoder estimates the sample amplitude values at the noninflection points by interpolating the received information. Simulation results show that the IPD method produces 7% mean square error improvement over the NUS method. With a small threshold to detect inflection points, the proposed coding method shows 0.38-8.72 dB signal-to-noise ratio (SNR) and 0.5-1.3 mean opinion score improvement, compared to the continuously variable slope delta modulation algorithm (CVSDM). The IPD method produces up to 8.5 dB improvement in SNR over the CVSDM at bit error rates (BER) below 5 × 10(-5), while the IPD method becomes worse than the CVSDM at BER above 5 × 10(-5).

Robust coding of wideband speech immittance spectral frequencies

In this paper, we propose a reduced complexity stochastic joint source-channel coding system developed for efficient and robust coding of wideband speech ISF (Immittance Spectral Frequency) parameters. Initially, the aim of this encoding system was to achieve a transparent quantization of ISF parameters for ideal transmissions over a noiseless channels. It was designed based on the switched split vector quantization (SSVQ) technique and called “ISF-SSVQ coder”. After that, our interest was drawn to the improvement of the ISF-SSVQ robustness for transmissions over a noisy channel. To protect implicitly our ISF coders, we developed a stochastic joint source-channel coding system based on a reduced complexity version of the channel optimized SSVQ technique. Simulation results will show that our new encoding system, called ISF-SCOSSVQ coder, can provide a good implicit protection to ISF parameters. The ISF-SCOSSVQ coder was further used to encode the ISF parameters of the Adaptive Multi-rate Wideband (AMR-WB, ITU-T G.722.2) speech coder operating over a noisy channel. We will show that the proposed ISF-SCOSSVQ coder contribute significantly in the improvement of the AMR-WB performance by ensuring a good coding robustness of its ISF parameters.

English

Compared to most digital data types, with the exception of digital audio, the data rates associated with uncompressed digital audio are substantial. Digital audio compression enables more efficient storage and transmission of audio data. The many forms of audio compression techniques offer a range of encoder and decoder complexity, compressed audio quality, and differing amounts of data compression. In this paper a new algorithm for speech signals compression using wavelet transform technique with Discrete Cosine Transform (DCT) technique. The performance of the implemented algorithm is evaluated based on Signal to Noise Ratio (SNR), Root Mean Square Error (MSE) and compression ratio tested on speech signals. In this paper a Wavelet & cosine hybrid model, based speech coder is implemented in software using Matlab.

Functional organization for musical consonance and tonal pitch hierarchy in human auditory cortex

Pitch relationships in music are characterized by their degree of consonance, a hierarchical perceptual quality that distinguishes how pleasant musical chords/intervals sound to the ear. The origins of consonance have been debated since the ancient Greeks. To elucidate the neurobiological mechanisms underlying these musical fundamentals, we recorded neuroelectric brain activity while participants listened passively to various chromatic musical intervals (simultaneously sounding pitches) varying in their perceptual pleasantness (i.e., consonance/dissonance). Dichotic presentation eliminated acoustic and peripheral contributions that often confound explanations of consonance. We found that neural representations for pitch in early human auditory cortex code perceptual features of musical consonance and follow a hierarchical organization according to music-theoretic principles. These neural correlates emerge pre-attentively within ~150ms after the onset of pitch, are segregated topographically in superior temporal gyrus with a rightward hemispheric bias, and closely mirror listeners' behavioral valence preferences for the chromatic tone combinations inherent to music. A perceptual-based organization implies that parallel to the phonetic code for speech, elements of music are mapped within early cerebral structures according to higher-order, perceptual principles and the rules of Western harmony rather than simple acoustic attributes.

An Efficient Search Strategy for ACELP Algebraic Codebook 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 (ACELP) speech coder. As the first step, individual pulse contribution in each track is given by RCM, and the number N of candidate pulses 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 to 4 pulses are carried out by a standard IFPR. Implemented on a G.729A speech codec, this proposal requires as few as 24 searches, a search load tantamount to 7.5% of G.729A, 37.5% of the global pulse replacement method (iteration=2), 50% 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. DOI: http://dx.doi.org/10.5755/j01.itc.43.2.4946

Experimental Analysis of Voice Ooze Algorithm using Voice-excited LPC Vocoder

This research paper examines the recent development in speech coding. Speech coding is a basic element of digital communications and constantly attracting attention due to the increase of power in telecommunication services and capabilities. This paper focuses on the design and implementation of a Voice-excited Linear Predictive coder at low bit-rate. And at last analyze result by using different voice examples. This research paper is divided into six divisions. General Terms Voice-excited LPC Vocoder et. al.

A memory efficient finite-state source coding algorithm for audio MDCT coefficients

To achieve a better trade-off between the vector dimension and the memory requirements of a vector quantizer (VQ), an entropy-constrained VQ (ECVQ) scheme with finite memory, called finite-state ECVQ (FS-ECVQ), is presented in this paper. The scheme consists of a finite-state VQ (FSVQ) and multiple component ECVQs. By utilizing the FSVQ, the inter-frame dependencies within source sequence can be effectively exploited and no side information needs to be transmitted. By employing the ECVQs, the total memory requirements of the FS-ECVQ can be efficiently decreased while the coding performance is improved. An FS-ECVQ, designed for the modified discrete cosine transform (MDCT) coefficients coding, was implemented and evaluated based on the Unified Speech and Audio Coding (USAC) scheme. Results showed that the FS-ECVQ achieved a reduction of the total memory requirements by about 11.3%, compared with the encoder in USAC final version (FINAL), while maintaining a similar coding performance.

Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range of the shift operator associated with the particular prediction problem considered. The second method uses the alternative Cauchy bound to impose a convex constraint on the predictor in the 1-norm error minimization. These methods are compared with two existing methods: the Burg method, based on the 1-norm minimization of the forward and backward prediction error, and the iteratively reweighted 2-norm minimization known to converge to the 1-norm minimization with an appropriate selection of weights. The evaluation gives proof of the effectiveness of the new methods, performing as well as unconstrained 1-norm based linear prediction for modeling and coding of speech.