This Small Business Innovation Research Phase I research project focuses on building current and next generation dialog systems by integrating automatic speech recognition (ASR) and state-of-the-art question answering (QA) technologies. Because of the very high cost, time required, and the complex design requirements and attendant technical expertise required to develop these systems, spoken dialog systems have had limited deployment. The technical objectives of this project are: automatic generation of context free grammars (CFGs) or statistical language models (SLMs) with minimum manual intervention; automatic tuning of CFGs or SLMs for improved ASR transcription accuracy; higher levels of transcription accuracy due to QA system-based filtering and feedback, and higher level phonetic and linguistic information sources; high levels of query response speed; natural speech input; precise and focused responses to user inputs. This project anticipates a significant reduction in the cost of developing applications due to the reduction of manual labor requirements, and improved accuracy due to the presence of higher level knowledge sources in required for the recognition and understanding of utterances.
The research project will result in a significant increase in deployment of spoken dialog applications due to reduced development costs and increased system accuracy. An increase in user satisfaction should follow from the reduction in user input constraints while maintaining high goal completion rates. Additionally, there should be an increased ease in modeling complicated tasks into spoken dialog systems.
