A robust CELP coder with source-dependent channel coding

A CELP coder using Source Dependent Channel Encoding (SDCE) for optimal channel error protection is introduced. With SDCE, each of the CELP parameters are encoded by minimizing a perceptually meaningful error criterion under prevalent channel conditions. Unlike conventional channel coding schemes, SDCE allows for optimal balance between error detection and correction. The experimental results show that the CELP system is robust under various channel bit error rates and displays a graceful degradation in SSNR as the channel error rate increases. This is a desirable property to have in a coder since the exact channel conditions cannot usually be specified a priori

A 4.8 kbps code-excited linear predictive coder

A secure voice system STU-3 capable of providing end-to-end secure voice communications (1984) was developed. The terminal for the new system will be built around the standard LPC-10 voice processor algorithm. The performance of the present STU-3 processor is considered to be good, its response to nonspeech sounds such as whistles, coughs and impulse-like noises may not be completely acceptable. Speech in noisy environments also causes problems with the LPC-10 voice algorithm. In addition, there is always a demand for something better. It is hoped that LPC-10's 2.4 kbps voice performance will be complemented with a very high quality speech coder operating at a higher data rate. This new coder is one of a number of candidate algorithms being considered for an upgraded version of the STU-3 in late 1989. The problems of designing a code-excited linear predictive (CELP) coder to provide very high quality speech at a 4.8 kbps data rate that can be implemented on today's hardware are considered

A variable rate speech compressor for mobile applications

One of the most promising speech coder at the bit rate of 9.6 to 4.8 kbits/s is CELP. Code Excited Linear Prediction (CELP) has been dominating 9.6 to 4.8 kbits/s region during the past 3 to 4 years. Its set back however, is its expensive implementation. As an alternative to CELP, the Base-Band CELP (CELP-BB) was developed which produced good quality speech comparable to CELP and a single chip implementable complexity as reported previously. Its robustness was also improved to tolerate errors up to 1.0 pct. and maintain intelligibility up to 5.0 pct. and more. Although, CELP-BB produces good quality speech at around 4.8 kbits/s, it has a fundamental problem when updating the pitch filter memory. A sub-optimal solution is proposed for this problem. Below 4.8 kbits/s, however, CELP-BB suffers from noticeable quantization noise as a result of the large vector dimensions used. Efficient representation of speech below 4.8 kbits/s is reported by introducing Sinusoidal Transform Coding (STC) to represent the LPC excitation which is called Sine Wave Excited LPC (SWELP). In this case, natural sounding good quality synthetic speech is obtained at around 2.4 kbits/s

Comparison of CELP speech coder with a wavelet method

This thesis compares the speech quality of Code Excited Linear Predictor (CELP, Federal Standard 1016) speech coder with a new wavelet method to compress speech. The performances of both are compared by performing subjective listening tests. The test signals used are clean signals (i.e. with no background noise), speech signals with room noise and speech signals with artificial noise added. Results indicate that for clean signals and signals with predominantly voiced components the CELP standard performs better than the wavelet method but for signals with room noise the wavelet method performs much better than the CELP. For signals with artificial noise added, the results are mixed depending on the level of artificial noise added with CELP performing better for low level noise added signals and the wavelet method performing better for higher noise levels

Quantisation mechanisms in multi-protoype waveform coding

Prototype Waveform Coding is one of the most promising methods for speech coding at low bit rates over telecommunications networks. This thesis investigates quantisation mechanisms in Multi-Prototype Waveform (MPW) coding, and two prototype waveform quantisation algorithms for speech coding at bit rates of 2.4kb/s are proposed. Speech coders based on these algorithms have been found to be capable of producing coded speech with equivalent perceptual quality to that generated by the US 1016 Federal Standard CELP-4.8kb/s algorithm. The two proposed prototype waveform quantisation algorithms are based on Prototype Waveform Interpolation (PWI). The first algorithm is in an open loop architecture (Open Loop Quantisation). In this algorithm, the speech residual is represented as a series of prototype waveforms (PWs). The PWs are extracted in both voiced and unvoiced speech, time aligned and quantised and, at the receiver, the excitation is reconstructed by smooth interpolation between them. For low bit rate coding, the PW is decomposed into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW). The SEW is coded using vector quantisation on both magnitude and phase spectra. The SEW codebook search is based on the best matching of the SEW and the SEW codebook vector. The REW phase spectra is not quantised, but it is recovered using Gaussian noise. The REW magnitude spectra, on the other hand, can be either quantised with a certain update rate or only derived according to SEW behaviours

Low bit rate speech coding methods and a new interframe differential coding scheme for line spectrum pairs

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1992.Thesis (Master's) -- Bilkent University, 1992.Includes bibliographical references leaves 30-32.Low bit rate speech coding techniques and a new coding scheme for vocal tract parameters are presented. Linear prediction based voice coding techniques (linear predictive coding and code excited linear predictive coding) are examined and implemented. A new interframe differential coding scheme for line spectrum pairs is developed. The new scheme reduces the spectral distortion of the linear predictive filter while maintaining a high compression ratio.Erzin, EnginM.S

A high quality voice coder with integrated echo canceller and voice activity detector for mobile satellite applications

In the last decade, low bit rate speech coding research has received much attention resulting in newly developed, good quality, speech coders operating at as low as 4.8 Kb/s. Although speech quality at around 8 Kb/s is acceptable for a wide variety of applications, at 4.8 Kb/s more improvements in quality are necessary to make it acceptable to the majority of applications and users. In addition to the required low bit rate with acceptable speech quality, other facilities such as integrated digital echo cancellation and voice activity detection are now becoming necessary to provide a cost effective and compact solution. In this paper we describe a CELP speech coder with integrated echo canceller and a voice activity detector all of which have been implemented on a single DSP32C with 32 KBytes of SRAM. The quality of CELP coded speech has been improved significantly by a new codebook implementation which also simplifies the encoder/decoder complexity making room for the integration of a 64-tap echo canceller together with a voice activity detector

DeepVoCoder: A CNN model for compression and coding of narrow band speech

This paper proposes a convolutional neural network (CNN)-based encoder model to compress and code speech signal directly from raw input speech. Although the model can synthesize wideband speech by implicit bandwidth extension, narrowband is preferred for IP telephony and telecommunications purposes. The model takes time domain speech samples as inputs and encodes them using a cascade of convolutional filters in multiple layers, where pooling is applied after some layers to downsample the encoded speech by half. The final bottleneck layer of the CNN encoder provides an abstract and compact representation of the speech signal. In this paper, it is demonstrated that this compact representation is sufficient to reconstruct the original speech signal in high quality using the CNN decoder. This paper also discusses the theoretical background of why and how CNN may be used for end-to-end speech compression and coding. The complexity, delay, memory requirements, and bit rate versus quality are discussed in the experimental results.Web of Science7750897508