Speech recognition for illiterate access to information and technology

In rural Tamil Nadu and other predominantly illiterate communities throughout the world, computers and technology are currently inaccessible without the help of a literate mediator. Speech recognition has often been suggested as a key to universal access, but success stories of speech-driven interfaces for illiterate end users are few and far between. The challenges of dialectal variation, multilingualism, cultural barriers, choice of appropriate content, and, most importantly, the prohibitive expense of creating the necessary linguistic resources for effective speech recognition are intractable using traditional techniques. This paper presents an inexpensive approach for gathering the linguistic resources needed to power a simple spoken dialog system. In our approach, data collection is integrated into dialog design: Users of a given village are recorded during interactions, and their speech semi-automatically integrated into the acoustic models for that village, thus generating the linguistic resources needed for automatic recognition of their speech. Our design is multi-modal, scalable, and modifiable. It is the result of an international, cross-disciplinary collaboration between researchers and NGO workers who serve the rural poor in Tamil Nadu. Our groundwork includes user studies, stakeholder interviews and field recordings of literate and illiterate agricultural workers in three districts of Tamil Nadu over the summer and fall of 2005. Automatic speech recognition experiments simulating the spoken dialog systems' performance during initialization and gradual integration of acoustic data informed the holistic structure of the design. Our research addresses the unique social and economic challenges of the developing world by relying on modifiable and highly transparent software and hardware, by building on locally available resources, and by emphasizing community operation and ownership through training and education.