Voice recognition system for Massey University Smarthouse : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Information Engineering at Massey University

The concept of a smarthouse aims to integrate technology into houses to a level where most daily tasks are automated and to provide comfort, safety and entertainment to the house residents. The concept is mainly aimed at the elderly population to improve their quality of life. In order to maintain a natural medium of communication, the house employs a speech recognition system capable of analysing spoken language, and extracting commands from it. This project focuses on the development and evaluation of a windows application developed with a high level programming language which incorporates speech recognition technology by utilising a commercial speech recognition engine. The speech recognition system acts as a hub within the Smarthouse to receive and delegate user commands to different switching and control systems. Initial trails were built using Dragon Naturally Speaking as the recognition engine. However that proved inappropriate for use in the Smarthouse project as it is speaker dependent and requires each user to train it with his/her own voice. The application now utilizes the Microsoft Speech Application Programming Interface (SAPI), a software layer which sits between applications and speech engines and the Microsoft Speech Recognition Engine, which is freely distributed with some Microsoft products. Although Dragon Naturally Speaking offers better recognition for dictation, MS engine can be optimized using Context Free Grammar (CFG) to give enhanced recognition in the intended application. The application is designed to be speaker independent and can handle continuous speech. It connects to a database oriented expert system to carry out full conversations with the users. Audible prompts and confirmations are achieved through speech synthesis using any SAPI compliant text to speech engine. Other developments focused on designing a telephony system using Microsoft Telephony Application Programming Interface (TAPI). This allows the house to be remotely controlled from anywhere in the world. House residents will be able to call their house from any part of the world and regardless of their location, the house will be able to respond to and fulfil their commands

An exploration of the potential of Automatic Speech Recognition to assist and enable receptive communication in higher education

The potential use of Automatic Speech Recognition to assist receptive communication is explored. The opportunities and challenges that this technology presents students and staff to provide captioning of speech online or in classrooms for deaf or hard of hearing students and assist blind, visually impaired or dyslexic learners to read and search learning material more readily by augmenting synthetic speech with natural recorded real speech is also discussed and evaluated. The automatic provision of online lecture notes, synchronised with speech, enables staff and students to focus on learning and teaching issues, while also benefiting learners unable to attend the lecture or who find it difficult or impossible to take notes at the same time as listening, watching and thinking

Multimodal person recognition for human-vehicle interaction

Next-generation vehicles will undoubtedly feature biometric person recognition as part of an effort to improve the driving experience. Today's technology prevents such systems from operating satisfactorily under adverse conditions. A proposed framework for achieving person recognition successfully combines different biometric modalities, borne out in two case studies

Spoken content retrieval: A survey of techniques and technologies

Speech media, that is, digital audio and video containing spoken content, has blossomed in recent years. Large collections are accruing on the Internet as well as in private and enterprise settings. This growth has motivated extensive research on techniques and technologies that facilitate reliable indexing and retrieval. Spoken content retrieval (SCR) requires the combination of audio and speech processing technologies with methods from information retrieval (IR). SCR research initially investigated planned speech structured in document-like units, but has subsequently shifted focus to more informal spoken content produced spontaneously, outside of the studio and in conversational settings. This survey provides an overview of the field of SCR encompassing component technologies, the relationship of SCR to text IR and automatic speech recognition and user interaction issues. It is aimed at researchers with backgrounds in speech technology or IR who are seeking deeper insight on how these fields are integrated to support research and development, thus addressing the core challenges of SCR