118 research outputs found

    A robust CELP coder with source-dependent channel coding

    Get PDF
    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

    Performance Comparison of AR Codebook Training for Speech Processing

    Get PDF

    Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

    Get PDF
    Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression

    Real-time digital speech transmission over the Internet

    Full text link
    This thesis describes a complete system for real-time digital speech communication over the Internet. A digital speech compressor is described, and a new real-time Internet protocol is designed. We focus on the mathematical representation of the system as well as its implementation providing pseudo-code routines for all components and algorithms. Our contribution stands in a combined solution to the problem that removes undesired properties, such as speech clipping and delay, that appeared in Internet real-time communication systems implemented in the past

    Energy Based Split Vector Quantizer Employing Signal Representation in Multiple Transform Domains.

    Get PDF
    This invention relates to representation of one and multidimensional signal vectors in nonorgothonal domains and design of Vector Quantizers that can be chosen among these representations. There is presented a Vector Quantization technique in multiple nonorthogonal domains for both waveform and model based signal characterization. An iterative codebook accuracy enhancement algorithm, applicable to both waveform and model based Vector Quantization in multiple nonorthogonal domains, which yields further improvement in signal coding performance, is disclosed. Further, Vector Quantization in in nonorthogonal domains is applied to speech and exhibits clear performance improvements of reconstruction quality for the same bit rate compared to existing single domain Vector Quantization techniques. The technique disclosed herein can be easily extended to several other one and multidimensional signal classes

    Apparatus And Quality Enhancement Algorithm For Mixed Excitation Linear Predictive (MELP) And Other Speech Coders

    Get PDF
    A system and method for enhancing the speech quality of the mixed excitation linear predictive (MELP) coder and other low bit-rate speech coders. The system and method employ a plosive analysis/synthesis method, which detects the frame containing a plosive signal, applies a simple model to synthesize the plosive signal, and adds the synthesized plosive to the coded speech. The system and method remains compatible with the existing MELP coder bit stream.Georgia-tech Research Corporatio

    Cell-Free XL-MIMO Meets Multi-Agent Reinforcement Learning: Architectures, Challenges, and Future Directions

    Full text link
    Cell-free massive multiple-input multiple-output (mMIMO) and extremely large-scale MIMO (XL-MIMO) are regarded as promising innovations for the forthcoming generation of wireless communication systems. Their significant advantages in augmenting the number of degrees of freedom have garnered considerable interest. In this article, we first review the essential opportunities and challenges induced by XL-MIMO systems. We then propose the enhanced paradigm of cell-free XL-MIMO, which incorporates multi-agent reinforcement learning (MARL) to provide a distributed strategy for tackling the problem of high-dimension signal processing and costly energy consumption. Based on the unique near-field characteristics, we propose two categories of the low-complexity design, i.e., antenna selection and power control, to adapt to different cell-free XL-MIMO scenarios and achieve the maximum data rate. For inspiration, several critical future research directions pertaining to green cell-free XL-MIMO systems are presented
    corecore