Improved speech analysis for glottal excited linear predictive speech coding

The authors describe an implementation of fast algorithms for codebook searching used in code-excited linear predictive (CELP) speech coding. They present details of the algorithms including (i) fast conversion of line spectrum pair parameters to linear predictive coding parameters, and (ii) fast searches of the parameters of adaptive and stochastic codebooks. The description can be readily used for CELP implementations, such as on (i) high-quality low-bit-rate speech transmission in point-to-point or store-and-forward mode, and (ii) efficient speech storage in speech recording and multimedia databases. The algorithms have been implemented on an IBM-PC AT equipped with a TMS320C30 module and a SUN Sparcstation 10 for the development of packet radio speech transmission and voice mail applications, respectively.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

By reconciling differences between the estimator and the filter of a code excited linear predictive (CELP) voice coder, higher quality is achieved in the output speech. The pulse amplitudes and pitch tap gain are solved for simultaneously to minimize the estimator bias in the CELP excitation. Increased signal to noise ratio is accomplished by modifying the pitch predictor such that the pitch synthesis filter accurately reflects the estimation procedure used to find the pitch tap gain, and by improving the excitation analysis technique such that the pitch predictor tap gain and codeword gain are solved for simultaneously, rather than sequentially. These modifications do not result in an increased transmission rate or significant increase in complexity of the CELP coding algorithm.

Electronic speech coding had its origin in 1928 when Homer Dudley proposed to send speech signals over a new transatlantic telegraph cable with the (then) enormous bandwidth of 100 Hz. Dudley argued that speech was generated by slowly moving articulators and should therefore require only some 100-Hz total bandwidth for transmission. Since extraction of these parameters proved difficult, Dudley suggested, as an alternative, the transmission of the likewise slowly changing spectral information. The result was the channel vocoder, which (together with formant and voice-excited vocoders) dominated speech coding and that of musical sounds of single-pitch instruments until the mid 1960s. Unhappy with the vocoder's “electronic accent.” Bishnu Atal and the author, in 1967, advanced the idea of linear predictive coding (LPC), motivated by the desire to replace rigid vocoderlike coding by a more flexible method in which a “prediction residual” could represent deviations of real speech signals from an assumed all-pole model. In 1972, subjective error criteria were introduced, based on auditory models of masking and the possibility of “hiding” quantizing noise under the speech signal. The resulting code-excited linear predictive (CELP) coders based on statistical models have been operated at 1/4 bit per sample for the residual at virtually no audible degradation. With powerful digital signal processing chips, CELP has now become the method of choice for synthetic-voice applications. For musical sounds, masking models and linear predictive coding, which is equivalent to prewhitening of the spectrum, lead to a substantial reduction in the required number of bits per sample.

From the Publisher: A great deal of modern communications equipment is being converted from analog to digital technology. This timely book explains many of the important concepts related to digital signal processing in easy-to-understand discussions of communications techniques, data transmission, filters, and hardware. Readers are given practical information on how to apply theory and algorithms to the design of radio receivers and transmitters. Among the areas discussed are analog to digital conversion - with emphasis on noise and distortion performance; manipulation of complex signals - positive and negative frequencies, plus Hilbert transformers; digital filters - guidelines for performance in communications, plus decimation and interpolation; hardware - multiplier accumulators, fast Fourier transform processors, digital signal processors, data flow techniques in equipment, and hardware simulation and testing; and speech processing - linear predictive coding (LPC), code excited linear predictive coding (CELP), and how to digitize speech at low data rates. Development of algorithms for oscillators, detectors, modulators, automatic gain control circuits, and other devices is clearly explained. Specific algorithms are provided for AM modulation, frequency modulation, FM detection, threshold extension, audio compression, automatic gain control, and squelch circuitry. Explanations of basic concepts of digital signal processing and data transmission are accompanied by reviews of signal representations, sampling, convolution, and z-transforms. Extensive real-world examples contribute to expertise in many facets of incorporating digital technology into devices. This hands-on treatment of DSP will help communications engineers upgrade their skills in digital signal processing and make a smooth transition into the design of more advanced systems. It also meets the needs of students who want to bolster their knowledge in communications.

In the last few years, Code-Excited Linear Predictive (CELP) coding has emerged as the most prominent technique for digital speech communication at rates of 8 Kb/s and below, and it is now considered the best candidate coder for digital mobile telephony and secure speech communication. While the CELP coder is able to provide fairly good-quality speech at 8 Kb/s, its performance at 4.8 Kb/s is yet unsatisfactory for many applications. The novelty in the CELP coding concept, namely, the stochastic excitation of a linear filter, also constitutes a weakness of this method: the excitation contains a noisy component which does not contribute to the speech synthesis process and can not be completely removed by the filter. It is a common opinion among speech communication researchers that new forms of excitations need to be studied in order to improve the CELP performance at low bit rates.

The aim of the study was to inspect the acoustic properties and sleep characteristics of a preapneic snoring sound. The feasibility of forecasting upcoming respiratory events by snoring sound was also investigated. Participants with habitual snoring or a heavy breathing sound during sleep were recruited consecutively. Polysomnography was conducted, and snoring-related breathing sound was recorded simultaneously. Acoustic features and sleep features were extracted from 30-second samples, and a machine learning algorithm was used to establish 2 prediction models. A total of 74 eligible participants were included. Model 1, tested by 5-fold cross-validation, achieved an accuracy of 0.92 and an area under the curve of 0.94 for respiratory event prediction. Model 2, with acoustic features and sleep information tested by Leave-One-Out cross-validation, had an accuracy of 0.78 and an area under the curve of 0.80. Sleep position was found to be the most important among all sleep features contributing to the performance of the 2 models. Preapneic sound presented unique acoustic characteristics, and snoring-related breathing sound could be deployed as a real-time apneic event predictor. The models, combined with sleep information, serve as a promising tool for an early warning system to forecast apneic events. Wang B, Yi X, Gao J, etal. Real-time prediction of upcoming respiratory events via machine learning using snoring sound signal. J Clin Sleep Med. 2021;17(9):1777-1784.

A modified regular-pulse excitation (RPE) linear predictive coding (LPC) codec is used to encode audio signals of 15 kHz bandwidth. With appropriate perceptual masking and carefully selected excitation structure, a fixed-pulse excitation (FPE) LPC codec is able to provide high-fidelity audio output. The quantization of both the LPC parameters and the excitation pulse sequence is examined. It is found that the LPC parameters can be quantized efficiently by adaptive differential PCM, while the excitation pulse sequences need more bits to quantize the amplitudes compared to narrowband speech encoding. Informal listening tests show that high-fidelity audio can be achieved at bit rates less than 100 kb/s.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The harmonic excitation linear predictive speech coder (HE-LPC) is a technique derived from MBE and MB-LPC type of speech coding algorithms. The HE-LPC coder has the potential of producing high quality speech at 4.8 kb/s and below. This coder employs a new pitch estimation and voicing technique. In addition, new DCT based LPC and residual amplitude quantization techniques have been developed. The 4 kb/s HE-LPC coder with a 14th order LPC filter was found to produce much better speech quality than the various low rate speech coding standards, including 3.6 kb/s INMARSAT Mini-M AMBE vocoder. During formal ITU ACR test, the 4 kb/s HE-LPC vocoder was found to produced equivalent performance to 32 kb/s ADPCM and G.729 for both flat and modified IRS filtered clean input speech conditions. The HE-LPC algorithm can also be extended to cover bit rates between 1.2 and 8 kb/s range depending on the application.

A testbench which enables a software implementation of different code-excited linear predictive (CELP) coder configurations in a simple and modular way, is presented as a research and development tool. It permits a flexible simulation process while using the actual hardware and software resources which constitute a real system. Its behaviour is consequently close to that of the final system envisaged. This testbench has been developed using the TMS320C30 digital signal processor and has been programmed in a modular way in C language. A CELP coder using two different codeword generation methods (the LBG algorithm and the Fuzzy-LVQ partitioning algorithm) have been tested using the proposed testbench.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Compared to scalar quantization (SQ), vector quantization (VQ) has memory, space-filling, and shape advantages. If the signal statistics are known, direct vector quantization (DVQ) according to these statistics provides the highest coding efficiency, but requires unmanageable storage requirements if the statistics are time varying. In code-excited linear predictive (CELP) coding, a single compromise codebook is trained in the excitation-domain and the space-filling and shape advantages of VQ are utilized in a nonoptimal, average sense. In this paper, we propose Karhunen-Loe/spl grave/ve transform (KLT)-based adaptive classified VQ (CVQ), where the space-filling advantage can be utilized since the Voronoi-region shape is not affected by the KLT. The memory and shape advantages can be also used, since each codebook is designed based on a narrow class of KLT-domain statistics. We further improve basic KLT-CVQ with companding. The companding utilizes the shape advantage of VQ more efficiently. Our experiments show that KLT-CVQ provides a higher SNR than basic CELP coding, and has a computational complexity similar to DVQ and much lower than CELP. With companding, even single-class KLT-CVQ outperforms CELP, both in terms of SNR and codebook search complexity.

Growth in Digital signal processing technology gives positives influences in human life. One of the branch of science that gives significant influence is digital speech processing. It can be expand into some applications that make human life easier. Digital speech processing is appropriate to speech recognition. Speech recognition is used to arrange the movement of remote control car. The remote control car will move according to our speech. This final project is closely related with speech recognition. The LPC (Linear Predictive Coding) method will extract the speech signal features and HMM (Hidden Markov Model) to modelling the speech signal are used. It is done by comparing model from extracting feature that is available in HMM modelling. Models will be used in the speech recognition process, if the models have highest level of conformity. The experiment has been done in two conditions, i.e ideal condition in room wih low noise level and unideal condition in room with noise. Result of the experiment from the whole sistem performace at ideal condition is 97,71% for people that have been inputed in the database, and 95,42% for people which have not been inputed in the database. Result of the experiment of database say it regulary is 97,14%. Result of the experiment of database at unideal condition is 54,28% for inputing word at noisy area, result of the experiment of database for inputing word at high frequency from siren voice is 98,57% and result of the experiment of inputing similar word with database is 97,6% Keywords: speech recognition, LPC, HMM

Although the speech quality of the code excited linear prediction (CELP) coder at 4800bit/s is relatively good, it is still perceived as rough or noisy. In the letter we propose a residual shaping method that produces, without signal distortion, quality comparable to that obtained by adaptive postfiltering. The proposed method is particularly effective in the multiple tandeming environment.

An error protection scheme for a vector-quantization (VQ)-based code excited linear predictive (CELP) coder for mobile radio applications is proposed. To arrive at an appropriate error protection strategy, the sensitivity of the different parameters in the CELP coder are studied, and then unequal error protection is designed according to parameter sensitivities. Different levels of error protection are provided by the use of punctured convolutional codes. The mobile radio channel is modeled as a Rayleigh fading channel. A convolutional interleaving technique is used to combat fading. The combined source and channel codec for this application has a total bit rate of 6.4 kb/s, of which 1.6 kb/s is used for channel coding. Simulation result show that the resulting codec can provide good quality speech at a Doppler frequency of 48 Hz and a channel bit error rate as high as 10/sup -2/. >

Code excited linear prediction (CELP) coding and its derivatives are currently the most frequently used techniques for speech compression at medium-to-low rate range. Until this study, the excitation vectors were always selected from a codebook generated by a Gaussian source or by the ensemble of residual signals collected from the used speech database. To the best of the author's knowledge, there is no study in which the excitation vectors were formed from a mixture of sources, a notion very successfully used by the speech recognition community within the hidden Markov model (HMM) framework. The authors proposed an improvement to the excitation model of CELP coders by embedding a labeled-state finite state vector quantization (FSVQ) and a mixture density approach in constructing 5-ms-long excitation vectors.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Trellis coded vector quantization (TCVQ) and code-excited linear prediction (CELP) coding are combined to form an efficient low-bit rate speech coding system. The resulting system uses a trellis search to select the synthesis filter excitation sequence, and is referred to as trellis excitation coding (TEC). Simulations are performed for encoding rates of 6.4 and 8 kbps. Informal listening tests indicate that the 8 kbps TEC system has quality roughly between that of 6-bit and 7-bit /spl mu/-law PCM with /spl mu/=255. The 6.4 kbps TEC system provides speech quality between 5-bit and 6-bit /spl mu/-law PCM. A subjective comparison with vector sum excited linear prediction (VSELP) indicates that the 8 kbps TEC and the VSELP reconstructed speech is about equally preferable.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>