The recent availability of large collections of text such as the Google 1T 5-gram corpus (Brants and Franz, 2006) and the Gigaword corpus of newswire (Graff, 2003) have made it po...
In this paper, we deal with information retrieval approach based on language model paradigm, which has been intensively investigated in recent years. We propose, implement, and ev...
This paper investigates the effectiveness of online temporal language model adaptation when applied to a Thai broadcast news transcription task. Our adaptation scheme works as fol...
We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the first pass uses...
In this paper, we propose a novel string-todependency algorithm for statistical machine translation. With this new framework, we employ a target dependency language model during d...
We propose a language model based on a precise, linguistically motivated grammar (a hand-crafted Head-driven Phrase Structure Grammar) and a statistical model estimating the proba...
An N-gram language model aims at capturing statistical word order dependency information from corpora. Although the concept of language models has been applied extensively to handl...
In this paper, a language model adapted to graph-based representation of image content is proposed and assessed. The full indexing and retrieval processes are evaluated on two diï...
In this paper, we address both standard and focused retrieval tasks based on comprehensible language models and interactive query expansion (IQE). Query topics are expanded using a...
Speech recognition of inflectional and morphologically rich languages like Czech is currently quite a challenging task, because simple n-gram techniques are unable to capture impo...