This paper is focused in the effect of adaptive weighted non-linearity in speech coding. The results showed that the effect of adaptive non-linearity improves the spectral distance measure when compared to the system without non-linearity. Key-Words: Coding, Non-linearity, Hammerstein Model, Adaptation

This paper describes the design and MOS performance of a family of low rate, low complexity speech coding algorithms known as Time Domain Voicing Cutoff (TDVC). TDVC is a predictive coding algorithm that employs a single transition frequency dividing voiced and unvoiced excitation. It provides the voicing flexibility of a frequency domain algorithm with lower complexity and rate overhead. A num...

We have seen rapid progress in high-quality compression of telephone speech and wideband speech signals. Linear prediction, subband coding, transform coding, as well as various forms of vector quantiza-tion and entropy coding techniques have been used to design efficient coding algorithms which can achieve substantially more compression than was thought possible only a few years ago. In the cas...

This paper presents a way of using a linear regression model to produce a single-valued criterion that indicates the perceived importance of each block in a stream of speech blocks. This method is superior to the conventional approach, voice activity detection (VAD), in that it provides a dynamically changing priority value for speech segments with finer granularity. The approach can be used in...

Low-bit-rate speech coding, at rates below 4 kb/s, is needed for both communication and voice storage applications. At such low rates, full encoding of the speech waveform is not possible; therefore, low-rate coders rely instead on parametric models to represent only the most perceptually-relevant aspects of speech. While there are a number of different approaches for this modeling, all can be ...

Digital speech communications are the future trend in the Internet and mobile phones. The low bit-rate coding of speech signals is the essential requirement in the concern of channel bandwidth and transmission efficiency. The voice-based services will become more attractive to the service providers. Many voice-driven applications require that users must be authorized and able to be identified. ...

In this paper, a novel solving method for speech signal chaotic time series prediction model was proposed. A phase space was reconstructed based on speech signal’s chaotic characteristics and the genetic programming (GP) algorithm was introduced for solving the speech chaotic time series prediction models on the phase space with the embedding dimension m and time delay . And then, the speech si...

Line spectral frequencies (LSF) are widely used in the field of speech coding. Due to its properties, the LSF are qualified for the quantisation and the efficient compression of speech signals. In this paper we introduce the line cepstral quefrencies (LCQ). They are derived from the cepstrum in the same manner as the LSF are derived from linear predictive coding (LPC) features. We show that the...

In this paper, we present a framework for developing source coding, channel coding and decoding as well as erasure concealment techniques adapted for distributed (wireless or packetbased) speech recognition. It is shown that speech recognition as opposed to speech coding, is more sensitive to channel errors than channel erasures, and appropriate channel coding design criteria are determined. Fo...

This paper proposes an architecture for low bit rate coding of noisy speech. The input noisy speech is decomposed into multiresolution signal components using wavelet transform. An iterative Wiener filtering is used at each level of wavelet analysis to enhance speech. The system model that evolves during enhancement is processed further to get optimal parameters for the quantization. A multista...