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A team of international researchers, led by Colorado State University’s Michael Gavin, have taken a first step in answering fundamental questions about human diversity.Humans collectively speak n...
String Kernels for Native Language Identification: Insights from Behind the Curtains
Text mining classification task depend on the characteristics of high level language features language task identity string
2016/10/31
The most common approach in text mining classification tasks is to rely on features like words, part-of-speech tags, stems, or some other high-level linguistic features. Recently, an approach that use...
Source Language Adaptation Approaches for Resource-Poor Machine Translation
Source Language Adaptation Approaches Resource-Poor Machine Translation
2016/7/7
Most of the world languages are resource-poor for statistical machine translation; still, many
of them are actually related to some resource-rich language. Thus, we propose three novel,
language-ind...
A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena
Computational Models Language Phenomena
2016/7/7
Word reordering is one of the most difficult aspects of statistical machine translation (SMT),
and an important factor of its quality and efficiency. Despite the vast amount of research
published to...
With recent advances in machine learning, big data, and computing infrastructure, computers will realistically reach human parity in understanding spoken language in the next few years. The computing ...
Language in its spoken form was invented over 50,000 years ago. Around that time, modern humans left their African homeland and colonized the entire planet. Writing was invented some 6,000 years ago, ...
Graph-Based Word Alignment for Clinical Language Evaluation
Graph-Based Word Alignment Clinical Language Evaluation
2016/2/23
Among the more recent applications for natural language processing algorithms has been the analysis of spoken language data for diagnostic and remedial purposes, fueled by the demand for simple, objec...
Feature-Frequency–Adaptive On-line Training for Fast and Accurate Natural Language Processing
Fast Accurate NaturalLanguage Processing
2015/9/14
Training speed and accuracy are two major concerns of large-scale natural language processing systems. Typically, we need to make a tradeoff between speed and accuracy. It is trivial to improve the tr...
Applications of Lexicographic Semirings to Problems in Speech and Language Processing
Lexicographic Semirings Speech and Language Processing
2015/9/14
This paper explores lexicographic semirings and their application to problems in speech and language processing. Specifically, we present two instantiations of binary lexicographic semirings, one invo...
Stochastic Language Generation in Dialogue using Factored Language Models
Stochastic Language Generation Dialogue Factored Language Models
2015/9/14
Most previous work on trainable language generation has focused on two paradigms: (a) using a generation decisions of an existing generator. Both approaches rely on the existence of a handcrafted gene...
Language Models for Machine Translation:Original vs. Translated Texts
Language Models Machine Translation Original vs.Translated Texts
2015/9/10
We investigate the differences between language models compiled from original target-language texts and those compiled from texts manually translated to the target language. Corroborating established ...
A Scalable Distributed Syntactic,Semantic,and Lexical Language Model
Distributed Syntactic Semantic Lexical
2015/9/10
This paper presents an attempt at building a large scale distributed composite language model that is formed by seamlessly integrating an n-gram model, a structured language model, and probabilistic l...
Levenshtein Distances Fail to Identify Language Relationships Accurately
Levenshtein Distances Fail Identify Language
2015/9/9
The Levenshtein distance is a simple distance metric derived from the number of edit operations needed to transform one string into another. This metric has received recent attention as a means of aut...
This article investigates the effects of different degrees of contextual granularity on language model performance. It presents a new language model that combines clustering and half-contextualization...
I had heard it said that Chomsky’s conception of language is at odds with the truth-conditional program in semantics. Some of my friends said it so often that the point—or at least a point—finally sun...