Articles

This paper presents an integrated, end-to-end approach to online spelling correction for text input. Online spelling correction refers to the spelling correction as you type, as opposed to post-editing. The online scenario is particularly important for languages that routinely use transliteration-based text input methods, such as Chinese and Japanese, because …...

This study presents a novel method that measures English language learners’ syntac- tic competence towards improving automated speech scoring systems. In contrast to most previous studies which focus on the length of production units such as the mean length of clauses, we focused on capturing the differ- ences in the …...

In this paper, we explore the classification of emotions in songs, using the music and the lyrics representation of the songs. We intro- duce a novel corpus of music and lyrics, con- sisting of 100 songs annotated for emotions. We show that textual and musical features can both be successfully …...

We present a novel beam-search decoder for grammatical error correction. The decoder iteratively generates new hypothesis correc- tions from current hypotheses and scores them based on features of grammatical correctness and fluency. These features include scores from discriminative classifiers for specific er- ror categories, such as articles and preposi- tions. …...

In this paper we address the problem of modeling compositional meaning for phrases and sentences using distributional methods. We experiment with several possible com- binations of representation and composition, exhibiting varying degrees of sophistication. Some are shallow while others operate over syntactic structure, rely on parameter learn- ing, or require …...

Most existing systems solved the phrase chunking task with the sequence labeling approaches, in which the chunk candidates cannot be treated as a whole during parsing process so that the chunk-level features cannot be exploited in a natural way. In this paper, we formulate phrase chunking as a joint segmentation …...

This paper addresses the task of construct- ing a timeline of events mentioned in a given text. To accomplish that, we present a novel representation of the temporal structure of a news article based on time intervals. We then present an algorithmic approach that jointly optimizes the temporal structure by …...

Topic models are increasingly being used for text analysis tasks, often times replacing ear- lier semantic techniques such as latent seman- tic analysis. In this paper, we develop a novel adaptive topic model with the ability to adapt topics from both the previous segment and the parent document. For this …...

Open Information Extraction (IE) systems ex- tract relational tuples from text, without re- quiring a pre-specified vocabulary, by iden- tifying relation phrases and associated argu- ments in arbitrary sentences. However, state- of-the-art Open IE systems such as REVERB and WOE share two important weaknesses – (1) they extract only relations …...

Evidence-based medicine is an approach whereby clinical decisions are supported by the best available findings gained from scien- tific research. This requires efficient access to such evidence. To this end, abstracts in evidence-based medicine can be labeled using a set of predefined medical categories, the so- called PICO criteria. This …...

In this paper, we propose a novel translation model (TM) based cross-lingual data selec- tion model for language model (LM) adapta- tion in statistical machine translation (SMT), from word models to phrase models. Given a source sentence in the translation task, this model directly estimates the probability that a sentence …...

In this paper, we propose a novel decoding al- gorithm for discriminative joint Chinese word segmentation, part-of-speech (POS) tagging, and parsing. Previous work often used a pipeline method – Chinese word segmentation followed by POS tagging and parsing, which suffers from error propagation and is unable to leverage information in …...

We introduce a novel coreference resolution system that models entities and events jointly. Our iterative method cautiously constructs clusters of entity and event mentions using lin- ear regression to model cluster merge opera- tions. As clusters are built, information flows between entity and event clusters through fea- tures that model …...

We introduce gap inheritance, a new struc- tural property on trees, which provides a way to quantify the degree to which intervals of de- scendants can be nested. Based on this prop- erty, two new classes of trees are derived that provide a closer approximation to the set of plausible …...

Distant supervision for relation extraction (RE) – gathering training data by aligning a database of facts with text – is an efficient ap- proach to scale RE to thousands of different relations. However, this introduces a challeng- ing learning scenario where the relation ex- pressed by a pair of entities …...

A forced derivation tree (FDT) of a sentence pair {f, e} denotes a derivation tree that can translate f into its accurate target translation e. In this paper, we present an approach that leverages structured knowledge contained in FDTs to train component models for statistical machine translation (SMT) systems. We …...

“Grounded” language learning employs train- ing data in the form of sentences paired with relevant but ambiguous perceptual contexts. B¨orschinger et al. (2011) introduced an ap- proach to grounded language learning based on unsupervised PCFG induction. Their ap- proach works well when each sentence po- tentially refers to one of …...

This paper proposes to generate appropriate answers for opinion questions about prod- ucts by exploiting the hierarchical organiza- tion of consumer reviews. The hierarchy orga- nizes product aspects as nodes following their parent-child relations. For each aspect, the re- views and corresponding opinions on this as- pect are stored. We …...

This paper present a new readability formula for French as a foreign language (FFL), which relies on 46 textual features representative of the lexical, syntactic, and semantic levels as well as some of the specificities of the FFL context. We report comparisons between sev- eral techniques for feature selection and …...

The Linked Data initiative comprises struc- tured databases in the Semantic-Web data model RDF. Exploring this heterogeneous data by structured query languages is tedious and error-prone even for skilled users. To ease the task, this paper presents a methodology for translating natural language questions into structured SPARQL queries over linked-data …...