Wireless Personal Area Network-Based Assistance for the Visually Impaired

In this dissertation, a system allowing a visually impaired person to interact with his environment is developed using modern, low-power wireless communications techniques. With recent advances in wireless sensor networks, open-source operating systems, and embedded processing technology, low-cost devices have become practically feasible as a personal notification system for impaired people. Additionally, text-to-speech capabilities can now be employed without special application specific integrated circuits (ASICs), allowing low-cost, general-purpose processors to fill a niche that once required expensive semiconductors. The system takes advantage of 802.15.4 and media access control (MAC) protocols offered by the open source operating system TinyOS. Important characteristics of these new standards that make them ideal for interface with humans are short range, low- power, and open-source software. To facilitate research and development in use and integration of such devices, we developed a hardware platform to allow exploration of possible future network architectures with multiple options for interfacing with the user. Our Visually Impaired Notification System (VINS) allows unprecedented awareness of the environment and has been simulated with multiple nodes using a modification of the TinyOS Dissemination protocol. This dissertation outlines the hardware platform, demonstration of a working prototype, and simulations of how the system would work in its intended environment. We envision this system being used as a testbed allowing further research of other communications and message-delivery techniques. Additionally, the research has contributed directly to the TinyOS project and offered new insight into power management in embedded systems. Finally, through the research effort we were able to contribute to the open source movement and have produced software in four languages used in three countries with over 1500 downloads

Speech Recognition

Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes