Bimasr: Framework for voice-based BIM information retrieval

Shin, S and Issa, R R A (2021) Bimasr: Framework for voice-based BIM information retrieval. Journal of Construction Engineering and Management, 147(10): 04021124, ISSN 0733-9364

Abstract

Voice is the most convenient means for human beings to communicate with others, even if the objects of their communication are not other humans but machines or computers. Many industries, and even the architecture, engineering, construction, and operations (AECO) industry, have attempted to study and apply speech recognition systems in their operations to improve work efficiency and productivity. However, previous studies on speech recognition had two limitations: they used keywords requiring basic knowledge of building information modeling (BIM) commands for using them and in searching BIM data, they relied on the Industry Foundation Classes (IFC) format, which involves converting BIM data to IFC. Such methods did not conduce to direct retrieval in BIM software. In the latter case, data search was possible, but data manipulation was not. To improve on the limitations of previous studies, this study developed a building information modeling automatic speech recognition (BIMASR) framework that requires no knowledge of BIM commands, which allows for the input of natural language (NL)-based questions into BIM software using human voice to search and manipulate data. The framework consists of three modules: one for voice recognition, one for natural language processing (syntax and semantic analysis), and one for BIM data preprocessing and interworking with relational databases. The manipulation of BIM data with NL-based s peech recognition converts the BIM operating environment from an expert-oriented into a user-oriented environment. This conversion allows for more BIM interaction and the popularization of BIM use and enhances the use of BIM in dynamic environments such as virtual reality, augmented reality, and holograms, where conventional input devices are typically absent.

Item Type: Article
Uncontrolled Keywords: building information modeling; domain ontology; information retrieval; natural language processing; speech recognition; structured query language
Index terms: relational database, ontology, augmented reality, efficiency, conversion, building information modelling, productivity, virtual reality, industry foundation classes, module, interaction, information retrieval
Subjects: visualization, virtual reality, computational design, behavioral psychology, information systems, data management, performance management, architectural elements, education and knowledge transfer, manufacturing engineering, management
Topics: Digital Applications, Design Practice, Quality Management, Business Strategy, Engineering Principles, Research Practice
Descriptive scope: 3 PCT

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here