Text to 3D Scene Generation with Rich Lexical Grounding

The ability to map descriptions of scenes to 3D geometric representations has many applications in areas such as art, education, and robotics. However, prior work on the text to 3D scene generation task has used manually specified object categories and language that identifies them. We introduce a dataset of 3D scenes annotated with natural language descriptions and learn from this data how to ground textual descriptions to physical objects. Our method successfully grounds a variety of lexical terms to concrete referents, and we show quantitatively that our method improves 3D scene generation over previous work using purely rule-based methods. We evaluate the fidelity and plausibility of 3D scenes generated with our grounding approach through human judgments. To ease evaluation on this task, we also introduce an automated metric that strongly correlates with human judgments.Comment: 10 pages, 7 figures, 3 tables. To appear in ACL-IJCNLP 201

Towards a Knowledge Graph based Speech Interface

Applications which use human speech as an input require a speech interface with high recognition accuracy. The words or phrases in the recognised text are annotated with a machine-understandable meaning and linked to knowledge graphs for further processing by the target application. These semantic annotations of recognised words can be represented as a subject-predicate-object triples which collectively form a graph often referred to as a knowledge graph. This type of knowledge representation facilitates to use speech interfaces with any spoken input application, since the information is represented in logical, semantic form, retrieving and storing can be followed using any web standard query languages. In this work, we develop a methodology for linking speech input to knowledge graphs and study the impact of recognition errors in the overall process. We show that for a corpus with lower WER, the annotation and linking of entities to the DBpedia knowledge graph is considerable. DBpedia Spotlight, a tool to interlink text documents with the linked open data is used to link the speech recognition output to the DBpedia knowledge graph. Such a knowledge-based speech recognition interface is useful for applications such as question answering or spoken dialog systems.Comment: Under Review in International Workshop on Grounding Language Understanding, Satellite of Interspeech 201

The positive side of a negative reference: the delay between linguistic processing and common ground

Interlocutors converge on names to refer to entities. For example, a speaker might refer to a novel looking object as the jellyfish and, once identified, the listener will too. The hypothesized mechanism behind such referential precedents is a subject of debate. The common ground view claims that listeners register the object as well as the identity of the speaker who coined the label. The linguistic view claims that, once established, precedents are treated by listeners like any other linguistic unit, i.e. without needing to keep track of the speaker. To test predictions from each account, we used visual-world eyetracking, which allows observations in real time, during a standard referential communication task. Participants had to select objects based on instructions from two speakers. In the critical condition, listeners sought an object with a negative reference such as not the jellyfish. We aimed to determine the extent to which listeners rely on the linguistic input, common ground or both. We found that initial interpretations were based on linguistic processing only and that common ground considerations do emerge but only after 1000 ms. Our findings support the idea that-at least temporally-linguistic processing can be isolated from common ground

Transitioning Applications to Semantic Web Services: An Automated Formal Approach

Semantic Web Services have been recognized as a promising technology that exhibits huge commercial potential, and attract significant attention from both industry and the research community. Despite expectations being high, the industrial take-up of Semantic Web Service technologies has been slower than expected. One of the main reasons is that many systems have been developed without considering the potential of the web in integrating services and sharing resources. Without a systematic methodology and proper tool support, the migration from legacy systems to Semantic Web Service-based systems can be a very tedious and expensive process, which carries a definite risk of failure. There is an urgent need to provide strategies which allow the migration of legacy systems to Semantic Web Services platforms, and also tools to support such a strategy. In this paper we propose a methodology for transitioning these applications to Semantic Web Services by taking the advantage of rigorous mathematical methods. Our methodology allows users to migrate their applications to Semantic Web Services platform automatically or semi-automatically

Social spatialization and everyday life

This editorial introduction discusses the problematic ‘demonology’ of spatial analyses that attempt to understand the logic of the social in terms of subject-based origins. Taking the poststructuralist notion of decentred subjectivity to task, it uses the metaphor of exorcism to approach everyday life as a haunted space. Instead of identifying the true demons behind the voices rendering an account of everyday life, it shifts methodological attention to the incommensurable multiplicity of traces through which we map and narrate a hermeneutics of becoming