We propose several techniques for improving statistical machine translation between closely-related languages with scarce resources. We use character-level translation trained on ...
Previous work using topic model for statistical machine translation (SMT) explore topic information at the word level. However, SMT has been advanced from word-based paradigm to p...
Xinyan Xiao, Deyi Xiong, Min Zhang, Qun Liu, Shoux...
In this paper, we extend our previous study on discriminative training using non-uniform criteria for speech recognition. The work will put emphasis on how the acoustic modeling i...
This paper presents an approach to estimating word level prominence in Swedish using syllable level features. The paper discusses the mismatch problem of annotations between word ...
In this paper we present the prototype based text matching methodology used in the Routing Sub-Task of TREC 2001 Filtering Track. The methodology examines texts on word and senten...
Ari Visa, Jarmo Toivonen, Tomi Vesanen, Jarno M&au...
Recently, categorical grammar has been focused as a powerful grammar. This paper aims to develop a framework for automatic CG tagging for Thai. We investigated two main algorithms...
Most of the Indian scripts do not have any robust commercial OCRs. Many of the laboratory prototypes report reasonable results at recognition/classification stage. However, word ...
Abstract. This paper presents an approach to large lexicon sign recognition that does not require tracking. This overcomes the issues of how to accurately track the hands through s...
— Reordered normal basis is a certain permutation of a type II optimal normal basis. In this paper, a high speed design of a word level finite field multiplier using reordered ...