Publications
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Context-Dependent Connectionist Probability Estimation in a Hybrid HMM-Neural Net Speech Recognition System
In this paper we present a training method and a network architecture for the estimation of context-dependent observation probabilities in the framework of a hybrid Hidden Markov Model (HMM) /…
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Integrating Neural Networks into Computer Speech Recognition Systems
The work described here involved integrating neural networks into a hidden Markov model-based state-of-the-art continuous-speech recognition system, resulting in improvements in recognition accuracy and reductions in model complexity.
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Semi-autonomous Mapmaking and Navigation
We describe an architecture of mobile robots based on the the concept of semi-autonomy that employs communication with a human advisor in order to simplify the tasks of map construction…
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Overview Of The SRI Cartographic Modeling Environment
The SRI Cartographic Modeling Environment has been created to support research on interactive, semi-automated, and automated computer-based cartographic activities. The underlying image manipulation capabilities are provided by the SRI ImagCalc…
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Learning By Collaborating: Convergent Conceptual Change
The goal of this article is to construct an integrated approach to collaboration and conceptual change. To this end, a case of conceptual change is analyzed from the point of…
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Multiple-State Context-Dependent Phonetic Modeling with MLPs
In this paper we present a new MLP architecture and training procedure for modeling context-dependent phonetic classes with a sequence of distributions.
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Camera self-calibration: theory and experiments
In this paper a complete method for calibrating a camera is presented. In contrast with existing methods it does not require a calibration object with a known 3D shape.
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Attachment Methods for Integration
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Reasoning with Analogical Representations
The framework consists of a set of generic operations on analogical structures and accompanying inference methods for integrating analogical and sentential information.
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Active head movements help solve stereo correspondance
Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC
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Combining Neural Networks and Hidden Markov Models for Continuous Speech Recognition
We present a speaker-independent, continuous-speech recognition system based on a hybrid multilayer perceptron (MLP)/hidden Markov model (HMM). The system combines the advantages of both approaches by using MLPs to estimate…
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Active Stereo with head movement