This work advances the state-of-the-art in assistive technology for the visually impaired by enhancing an automated tutor designed to teach beginner-level braille writing skills. The hardware component of the tutor is a low-cost device that provides an intelligent tactile interface that connects to a laptop or desktop computer. We demonstrate the many uses of this tutor including its multilingual capabilities, interactive exercises, and educational games. Preliminary field tests of the tutor in India, Zambia, and Qatar have demonstrated the usefulness of this automated tutor, and its potential to enhance braille literacy in developing regions.

The reported work advances the state-of-the-art in assistive technology for the blind by enhancing a low-cost automated tutor designed to teach Braille writing skills to visually impaired children using voice feedback. We first provide some background on how the methodology of Intelligent Tutoring Systems correlates to an automated tutor for teaching Braille writing skills. We then build on prior work to enhance our automated Braille Writing Tutor in three dimensions: (1) Initial field testing in three different countries; (2) Exploring customization needs for improving relevance in different cultures; and (3) Adding relevant games for increasing motivation. The outcome of this work is an enhanced low-cost tool that can help to increase Braille literacy in blind communities around the world.

We study the round complexity of two-party protocols for generating a random n-bit string such that the output is guaranteed to have bounded “bias,” even if one of the two parties deviates from the protocol (possibly using unlimited computational resources). Specifically, we require that the output's statistical difference from the uniform distribution on $\{0,1\}^n$ is bounded by a constant less than 1. We present a protocol for the above problem that has $2 \log^* n + O(1)$ rounds, improving a previous $2n$-round protocol of Goldreich, Goldwasser, and Linial (FOCS '91). Like the GGL Protocol, our protocol actually provides a stronger guarantee, ensuring that the output lands in any set $T \subseteq \{0,1\}^n$ of density $\mu$ with probability at most $O(\sqrt{\mu + \delta})$, where $\delta$ may be an arbitrarily small constant. We then prove a nearly matching lower bound, showing that any protocol guaranteeing bounded statistical difference requires at least $\log^* n - \log^* \log^* n - O(1)$ rounds. We also prove several results for the case when the output's bias is measured by the maximum multiplicative factor by which a party can increase the probability of a set $T \subseteq \{0,1\}^n$.

We study the round complexity of two-party protocols for generating a random n-bit string such that the output is guaranteed to have bounded bias (according to some measure) even if one of the two parties deviates from the protocol (even using unlimited computational resources). Specifically, we require that the output's statistical difference from the uniform distribution on zon is bounded by a constant less than 1.We present a protocol for the above problem that has 2 log*n+O(1) rounds, improving a 2n-round protocol that follows from the work of Goldreich, Goldwasser, and Linial (FOCS'91). Like the GGL protocol, our protocol actually provides a stronger guarantee, ensuring that the output lands in any set T⊆zon of density μ with probability at most O(√μ+δ), where δ is an arbitarily small constant.We then prove a matching lower bound, showing that any protocol guaranteeing bounded statistical difference requires at least log*n - log* log*n-O(1) rounds. As far as we know, this is the first nontrivial lower bound on the round complexity of random selection protocols (of any type) that does not impose additional constraints (e.g. on communication or "simulatability").We also state several results for the case when the output's bias is measured by the maximum multiplicative factor by which a party can increase the probability of a set T ⊆ zon.