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-The well-known Baum-Eagon inequality I31 provides an effective iterative scheme for finding a local maximum for homogeneous polynomials with positive coefticients over a domain of probability values. However, in many applications we are interested in maximizing a general rational function. We extend the Baum-Eagon inequality to rational functions. We briefly describe some of the applications of this inequality to statistical estimation problems.

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In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training examples, similar to k-nearest neighbor (kNN) and Support Vector Machines (SVMs). However, unlike SVMs and kNNs, CS allows the number of supports to be adapted to the specific signal being characterized. On the TIMIT phonetic classification task, we find that our CS method outperforms the SVM, kNN and Gaussian Mixture Model (GMM) methods. Our CS method achieves an accuracy of 80.01%, one of the best reported result in the literature to date.

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Accessibility in the workplace and in academic settings has increased dramatically for users with disabilities, driven by greater awareness, legislative mandate, and technological improvements. Gaps, however, remain. For persons who are deaf and hard of hearing in particular, full participation requires complete access to audio materials, both for live settings and for prerecorded audio and visual information. Even for users with adequate hearing, captioned or transcribed materials offer another modality for information access, one that can be particularly useful in certain situations, such as listening in noisy environments, interpreting speakers with strong accents, or searching audio media for specific information. Providing this level of access through fully automated means is currently beyond the state of the art. This paper details a number of key advances in audio access that have occurred over the last five years. We describe the Liberated Learning Project, a consortium of universities worldwide, which is piloting technologies to create real-time access for students who are deaf and hard of hearing, without intermediary assistance. In support of this project, IBM Research has created the ViaScribee tool that converts speech recognition output to a viable captioning interface. Additional inventions and incremental improvements to speech recognition for captioning are described, as well as future directions.

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