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Translation models used for statistical machine translation are compiled from parallel corpora that are manually translated. The common assumption is that parallel texts are symmetrical: The direction...
Targeted paraphrasing is a new approach to the problem of obtaining cost-effective, reasonable quality translation that makes use of simple and inexpensive human computations by monolingual speakers i...
Choi, Wiemer-Hastings, and Moore (2001) proposed to use Latent Semantic Analysis (LSA) to extract semantic knowledge from corpora in order to improve the accuracy of a text segmentation algorithm. B...
We present a novel method for discovering parallel sentences in comparable, non-parallel corpora.We train a maximum entropy classifier that, given a pair of sentences, can reliably determine whether o...
We examine how differences in language models, learned by different data-driven systems performing the same NLP task, can be exploited to yield a higher accuracy than the best individual system. We do...
Aspectual classification maps verbs to a small set of primitive categories in order to reason abouttime. This classification is necessary for interpreting temporal modifiers and assessing temporal rel...
Pronunciation by analogy (PbA) is a data-driven method for relating letters to sound, with potential application to next-generation text-to-speech systems. This paper extends previous work on PbA in...
Machine Translation for Indian languages is an emerging research area. Transliteration is one such module that we design while designing a translation system. Transliteration means mapping of source l...
Despite efforts to build robust vision systems, robots in new environments inevitably encounter new objects. Traditional supervised learning requires gathering and annotating sample images in the envi...
武汉理工大学英语写作英文课件Chapter2 Improving Paragraph Skills。
This paper presents a Native Language Identification (NLI) system based on TF-IDF weighting schemes and using linear classifiers - support vector machines, logistic regressions and perceptrons. The sy...
Using Untranscribed User Utterances for Improving Language Models based on Confidence Scoring.
Improving Nonnative Speech Understanding Using Context and N-Best Meaning Fusion.

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