#Blocksworld speech functions full

Inspired a flurry of projects on visual reasoning. The CLEVR dataset and its modified versions, such as ,Д¬an be viewed as a response to this kind of semantic obliquity in prior work, since it lays out an explicit spatial question answering challenge. Though aimed at goals quite different from ours, their framework, like ours, includes physical blocks on a table, Kinect cameras that capture the scene, speech communication, and a commitment to deriving utterance meanings that fit into a comprehensive approach to meaning representation. Their studies are focused on learning spatial concepts in the blocks world (such as staircases, towers, etc.) based on verbally-conveyed structural constraints, e.g., вЂњThe height is at most 3вЂќ, as well as explicit examples and counterexamples, given by user, that help the system to zero in on the correct set of constraints that define the structure class. Modern efforts in blocks world spatial language, in a similar spirit as ours, include work by Perera et al.

The latter was focused on construction planning, rather than user interaction, and as such incorporated extensive reasoning about geometric consistency and structural stability, more than descriptive aspects of the block configurations. Related WorkД®arly studies featuring the blocks world include and, both of which relied on a simulated environment.

#Blocksworld speech functions full

READ FULL TEXT VIEW PDFДЄs will be seen in the following sections, our system is distinctive in that (1) it is an end-to-end system using computer vision and spoken dialogue with an on-screen virtual human (2) it did not require a large training corpus, only a modest development corpus using naturally posed spatial questions by a few participants (3) the development of the semantic parser took only a few weeks вЂ“ no more, we infer, than semantic parsers developed for NN-based spatial QA studies yet it produces logical forms consistent with a comprehensive approach to English logical form, rather than producing specialized procedures, like some of the most nearly comparable systems (4) the system models the perceived scene in 3D graphics (5) the constraint-based spatial relation models are realistic, rather than artificially simplified, as for example in many CLEVR-based studies (6) scenes and the dialogues are real, rather than synthetic and (7) quite good results are achieved with symbolic and soft constraint-solving methods alone. Multi-modal human-computer interaction pipeline. These and other components are integrated into a Meaning representation, a dialog manager based on a schema representation, andДЄ constraint solver for spatial questions that provides answers in agreement Maps spatial questions into logical forms consistent with a general approach to The contributions of this work include a semantic parser that

Spatial queries, and a constraint solver that derives answers based on 3-D Mediated by an animated avatar, a dialogue system that robustly interprets In this work we tackle spatial questionДЄnswering in a holistic way, using a vision system, speech input and output There is currently a resurgence of interest in solving problems in such limitedДomains using modern techniques. Despite its relative simplicity, tackling thisДomain in its full complexity requires the agent to exhibit a rich set ofДЇunctional capabilities, ranging from vision to natural language understanding. The blocks world is a classic toy domain that has long been used to build and A Spoken Dialogue System for Spatial Question Answering in a Physical