An upper bound is given on the cutoff rate of discrete memoryless channels. This upper bound, which coincides with a known lower bound, determines the cutoff rate, and settles a long-standing open problem.

In [1] we derived one shot achievable and converse bounds with possible mismatched decoding. In this paper, we extend the results to the list decoding case.

Reconstructing stimuli from the spike trains of neurons is an important approach for understanding the neural code. One of the difficulties associated with this task is that signals which are varying continuously in time are encoded into sequences of discrete events or spikes. An important problem is to determine how much information about the continuously varying stimulus can be extracted from...

This paper describes continuous speech recognition incorporating the additional complement information, e.g., voice characteristics, speaking styles, linguistic information and noise environment, into HMM-based acoustic modeling. In speech recognition systems, contextdependent HMMs, i.e., triphone, and the tree-based context clustering have commonly been used. Several attempts to utilize not on...

We present a hierarchical statistical machine translation system which supports discontinuous constituents. It is based on synchronous linear context-free rewriting systems (SLCFRS), an extension to synchronous context-free grammars in which synchronized non-terminals span k ≥ 1 continuous blocks on either side of the bitext. This extension beyond contextfreeness is motivated by certain complex...

Recently, minimum perfect hashing (MPH)-based language model (LM) lookup methods have been proposed for fast access of N-gram LM scores in lexical-tree based LVCSR (large vocabulary continuous speech recognition) decoding. Methods of node-based LM cache and LM context pre-computing (LMCP) have also been proposed to combine with MPH for further reduction of LM lookup time. Although these methods...

For machine translation to tackle discourse phenomena, models must have access to extrasentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, d...

One problem with phrase-based statistical machine translation is the problem of longdistance reordering when translating between languages with different word orders, such as Japanese-English. In this paper, we propose a method of imposing reordering constraints using document-level context. As the documentlevel context, we use noun phrases which significantly occur in context documents contain...

In this paper, we introduce several hybrid connectionist-structural acoustic models for context-independent phone-like units. The structural part has been modeled with Markov chains or nite state networks learned by grammatical inference techniques. A multilayer perceptron or a committee of multilayer perceptrons is used to estimate the emission probabilities of the structural models. We compar...

We provide an analysis of the turbo decoding algorithm (TDA) in a setting involving Gaussian densities. In this context, we are able to show that the algorithm converges and that somewhat surprisingly though the density generated by the TDA may differ significantly from the desired posterior density, the means of these two densities coincide.