Phrase

About: Phrase is a research topic. Over the lifetime, 12580 publications have been published within this topic receiving 317823 citations. The topic is also known as: syntagma & phrases.

Using a Dependency Parser to Improve SMT for Subject-Object-Verb Languages

Abstract: We introduce a novel precedence reordering approach based on a dependency parser to statistical machine translation systems. Similar to other preprocessing reordering approaches, our method can efficiently incorporate linguistic knowledge into SMT systems without increasing the complexity of decoding. For a set of five subject-object-verb (SOV) order languages, we show significant improvements in BLEU scores when translating from English, compared to other reordering approaches, in state-of-the-art phrase-based SMT systems.

The effectiveness of a nonsyntatic approach to automatic phrase indexing for document retrieval

Abstract: It may be possible to improve the quality of automatic indexing systems by using complex descriptors, for example, phrases, in addition to the simple descriptors (words or word stems) that are normally used in automatically constructed representations of document content. This study is directed toward the goal of developing effective methods of identifying phrases in natural language text from which good quality phrase descriptors can be constructed. The effectiveness of one method, a simple nonsyntactic phrase indexing procedure, has been tested on five experimental document collections. The results have been analyzed in order to identify the inadequacies of the procedure, and to determine what kinds of information about text structure are needed in order to construct phrase descriptors that are good indicators of document content. Two primary conclusions have been reached: (1) In the retrieval experiments, the nonsyntactic phrase construction procedure did not consistently yield substantial improvements in effectiveness. It is therefore not likely that phrase indexing of this kind will prove to be an important method of enhancing the performance of automatic document indexing and retrieval systems in operational environments. (2) Many of the shortcomings of the nonsyntactic approach can be overcome by incorporating syntactic information into the phrase construction process. However, a general syntactic analysis facility may be required, since many useful sources of phrases cannot be exploited if only a limited inventory of syntactic patterns can be recognized. Further research should be conducted into methods of incorporating automatic syntactic analysis into content analysis for document retrieval. © 1989 John Wiley & Sons, Inc.

“That's So Gay!”: Examining the Covariates of Hearing This Expression Among Gay, Lesbian, and Bisexual College Students

Abstract: Objective: The investigators examined the health and well-being correlates of hearing the popular phrase “that's so gay” among gay, lesbian, and bisexual (GLB) emerging adults. Participants: Participants were 114 self-identified GLB students aged 18 to 25 years. Methods: An online survey was distributed to students at a large public university in the Midwest during winter 2009. Results: Participants’ social and physical well-being was negatively associated with hearing this phrase, specifically feeling isolated and experiencing physical health symptoms (ie, headaches, poor appetite, or eating problems). Conclusions: College professionals and student leaders must acknowledge that the phrase is a form of heterosexist harassment. As such, policies addressing diversity and harassment should address students’ use of this phrase, aiming to reduce its use. Additionally, colleges and universities should develop practices that counteract poorer well-being associated with hearing the phrase.

Speaker Independent Emotion Recognition by Early Fusion of Acoustic and Linguistic Features within Ensembles

Abstract: Herein we present a comparison of novel concepts for a robust fusion of prosodic and verbal cues in speech emotion recognition. Thereby 276 acoustic features are extracted out of a spoken phrase. For linguistic content analysis we use the Bag-of-Words text representation. This allows for integration of acoustic and linguistic features within one vector prior to a final classification. Extensive feature selection by filter- and wrapper based methods is fulfilled. Likewise optimal sets via SVM-SFFS and single feature relevance by information gain ratio calculation are presented. Overall classification is realised by diverse ensemble approaches. Among base classifiers Kernel Machines, Decision Trees, Bayesian classifiers, and memory-based learners are found. Acoustics only tests ran on a database comprising 39 speakers for speaker independent accuracy analysis. Additionally the public Berlin Emotional Speech database is used. A further database of 4,221 movie related phrases forms the basis of acoustic and linguistic information analysis evaluation. Overall remarkable performance in the discrimination of seven discrete emotions could be observed.

Query-Guided Regression Network with Context Policy for Phrase Grounding

Abstract: Given a textual description of an image, phrase grounding localizes objects in the image referred by query phrases in the description. State-of-the-art methods address the problem by ranking a set of proposals based on the relevance to each query, which are limited by the performance of independent proposal generation systems and ignore useful cues from context in the description. In this paper, we adopt a spatial regression method to break the performance limit, and introduce reinforcement learning techniques to further leverage semantic context information. We propose a novel Query-guided Regression network with Context policy (QRC Net) which jointly learns a Proposal Generation Network (PGN), a Query-guided Regression Network (QRN) and a Context Policy Network (CPN). Experiments show QRC Net provides a significant improvement in accuracy on two popular datasets: Flickr30K Entities and Referit Game, with 14.25% and 17.14% increase over the state-of-the-arts respectively.