Articles

Sociolinguists have long argued that social context influences language use in all manner of ways, resulting in lects 1. This paper ex- plores a text classification problem we will call lect modeling, an example of what has been termed computational sociolinguistics. In particular, we use machine learning techniques to identify …...

In this work we address the task of computer- assisted assessment of short student answers. We combine several graph alignment features with lexical semantic similarity measures us- ing machine learning techniques and show that the student answers can be more accu- rately graded than if the semantic measures were used …...

We investigate whether wording, stylistic choices, and online behavior can be used to predict the age category of blog authors. Our hypothesis is that significant changes in writing style distinguish pre-social me- dia bloggers from post-social media blog- gers. Through experimentation with a range of years, we found that the …...

The automatic coding of clinical documents is an important task for today’s healthcare providers. Though it can be viewed as multi-label document classification, the cod- ing problem has the interesting property that most code assignments can be supported by a single phrase found in the input docu- ment. We propose …...

In this paper, we adopt an n-best rescoring scheme using pitch-accent patterns to improve automatic speech recognition (ASR) perfor- mance. The pitch-accent model is decoupled from the main ASR system, thus allowing us to develop it independently. N-best hypothe- ses from recognizers are rescored by addi- tional scores that measure …...

This paper focuses on identifying, extracting and evaluating features related to syntactic complexity of spontaneous spoken responses as part of an effort to expand the current feature set of an automated speech scoring system in order to cover additional aspects considered important in the construct of communicative competence. Our goal …...

Large vocabulary speech recognition systems fail to recognize words beyond their vocab- ulary, many of which are information rich terms, like named entities or foreign words. Hybrid word/sub-word systems solve this problem by adding sub-word units to large vo- cabulary word based systems; new words can then be represented by …...

Unrehearsed spoken language often contains disfluencies. In order to correctly inter- pret a spoken utterance, any such disfluen- cies must be identified and removed or other- wise dealt with. Operating on transcripts of speech which contain disfluencies, we study the effect of language model and loss func- tion on the …...

Counts from large corpora (like the web) can be powerful syntactic cues. Past work has used web counts to help resolve isolated am- biguities, such as binary noun-verb PP attach- ments and noun compound bracketings. In this work, we first present a method for gener- ating web count features that …...

CCGs are directly compatible with binary- branching bottom-up parsing algorithms, in particular CKY and shift-reduce algorithms. While the chart-based approach has been the dominant approach for CCG, the shift-reduce method has been little explored. In this paper, we develop a shift-reduce CCG parser using a discriminative model and beam search, …...

We develop a general dynamic programming technique for the tabulation of transition-based dependency parsers, and apply it to obtain novel, polynomial-time algorithms for parsing with the arc-standard and arc-eager models. We also show how to reverse our technique to ob- tain new transition-based dependency parsers from existing tabular methods. Additionally, …...

Dependency parsing is a central NLP task. In this paper we show that the common eval- uation for unsupervised dependency parsing is highly sensitive to problematic annotations. We show that for three leading unsupervised parsers (Klein and Manning, 2004; Cohen and Smith, 2009; Spitkovsky et al., 2010a), a small set …...

Community-based question answer (Q&A) has become an important issue due to the pop- ularity of Q&A archives on the web. This pa- per is concerned with the problem of ques- tion retrieval. Question retrieval in Q&A archives aims to find historical questions that are semantically equivalent or relevant to the …...

While it is generally accepted that many trans- lation phenomena are correlated with linguis- tic structures, employing linguistic syntax for translation has proven a highly non-trivial task. The key assumption behind many ap- proaches is that translation is guided by the source and/or target language parse, employ- ing rules extracted …...

We present an unsupervised model for joint phrase alignment and extraction using non- parametric Bayesian methods and inversion transduction grammars (ITGs). The key con- tribution is that phrases of many granulari- ties are included directly in the model through the use of a novel formulation that memorizes phrases generated not …...

In this paper, we present an unsupervised framework that bootstraps a complete corefer- ence resolution (CoRe) system from word as- sociations mined from a large unlabeled cor- pus. We show that word associations are use- ful for CoRe – e.g., the strong association be- tween Obama and President is an …...

We describe a novel approach for inducing unsupervised part-of-speech taggers for lan- guages that have no labeled training data, but have translated text in a resource-rich lan- guage. Our method does not assume any knowledge about the target language (in par- ticular no tagging dictionary is assumed), making it applicable …...

Compositional question answering begins by mapping questions to logical forms, but train- ing a semantic parser to perform this mapping typically requires the costly annotation of the target logical forms. In this paper, we learn to map questions to answers via latent log- ical forms, which are induced automatically from …...

Negation is present in all human languages and it is used to reverse the polarity of part of statements that are otherwise affirmative by default. A negated statement often carries pos- itive implicit meaning, but to pinpoint the pos- itive part from the negative part is rather dif- ficult. This …...

Resolving polysemy and synonymy is re- quired for high-quality information extraction. We present ConceptResolver, a component for the Never-Ending Language Learner (NELL) (Carlson et al., 2010) that handles both phe- nomena by identifying the latent concepts that noun phrases refer to. ConceptResolver per- forms both word sense induction and synonym …...