One way to save the power consumption in the H.264 decoder is for the H.264 encoder to generate decoderfriendly bit streams. By following this idea, a decoding complexity model of context-based adaptive binary arithmetic coding (CABAC) for H.264/AVC is investigated in this research. Since different coding modes will have an impact on the number of quantized transformed coefficients (QTCs) and m...

This paper describes a modified composition algorithm that is used for combining two finite-state transducers, representing the context-dependent lexicon and the language model respectively, in large vocabulary speech recogntion. This algorithm is a hybrid between the static and dynamic expansion of the resultant transducer, which maps from context-dependent phones to words and is searched duri...

Motivated by its success in decoding turbo codes, we provide an analysis of the belief propagation algorithm on the turbo decoding graph with Gaussian densities. In this context, we are able to show that, under certain conditions, the algorithm converges and that – somewhat surprisingly – though the density generated by belief propagation may differ significantly from the desired posterior dens...

Recently, attention mechanism based deep learning has gained much popularity in speech recognition and natural language processing due to its flexibility at the decoding phase. Through the attention mechanism, the relevant encoding context vectors contribute a majority portion to the construction of the decoding context, while the effect of the irrelevant ones is minimized. Inspired by this ide...

Information coding in the Central Nervous System (CNS) remains unexplored. There is mounting evidence that, even at a very low level, the representation of a given stimulus might be dependent on context and history. If this is actually the case, bi-directional interactions between the brain (or if need be a reduced model of it) and sensory-motor system can shed a light on how encoding and decod...

In this paper, two new hybrid algorithms are proposed for decoding Low Density Parity Check (LDPC) codes. Original version of the proposed algorithms named Search Based Weighted Multi Bit Flipping (SWMBF). The main idea of these algorithms is flipping variable multi bits in each iteration, change in which leads to the syndrome vector with least hamming weight. To achieve this, the proposed algo...

An improved Context-based Adaptive Binary Arithmetic Coding (CABAC) is presented in the paper. The idea for the improvement is to use a more accurate mechanism for estimation of symbol probabilities in the standard CABAC algorithm. The authors’ proposal of such a mechanism is based on the Context-Tree Weighting (CTW) technique. In the framework of HEVC video encoder the improved CABAC allows 1....

A method for incorporating context-dependent phone classes in a connectionist-HMM hybrid speech recognition system is introduced. A modular approach is adopted, where single-layer networks discriminate between different context classes given the phone class and the acoustic data. The context networks are combined with a context-independent (CI) network to generate context-dependent (CD) phone p...

In this paper we describe a word reordering strategy for statistical machine translation that reorders the source side based on Part of Speech (POS) information. Reordering rules are learned from the word aligned corpus. Reordering is integrated into the decoding process by constructing a lattice, which contains all word reorderings according to the reordering rules. Probabilities are assigned ...