Harry Printz

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Ciprian Chelba David Engle Frederick Jelinek Victor Jimenez Sanjeev Khudanpur Lidia Mangu Harry Printz Eric Ristad Ronald Rosenfeld Andreas Stolcke Dekai Wu Johns Hopkins University Baltimore, MD Department of Defense Fort Meade, MD U Politecnica de Valencia Valencia, Spain IBM Watson Research Center Yorktown Heights, NY Princeton University Princeton, NJ(More)
In this paper we define two alternatives to the familiar perplexity statistic (hereafter lexical perplexity), which is widely applied both as a measure-of-goodness and as an objective function for training language models. These alternatives, respectively acoustic perplexity and the synthetic acoustic word error rate, fuse information from both the language(More)
In this paper we study the gain a naturally arising statistic from the theory of memd modeling as a gure of merit for selecting features for an memd language model We compare the gain with two popular alternatives empirical activation and mutual information and argue that the gain is the preferred statistic on the grounds that it directly measures a fea(More)
We describe an implementation of a simple probabilistic link grammar. This probabilistic language model extends trigrams by allowing a word to be predicted not only from the two immediately preceeding words, but potentially from any preceeding pair of adjacent words that lie within the same sentence. In this way, the trigram model can skip over less(More)
This paper describes a robust, accurate, efficient, low-resource, medium-vocabulary, grammar-based speech recognition system using Hidden Markov Models for mobile applications. Among the issues and techniques we explore are improving robustness and efficiency of the front-end, using multiple microphones for removing extraneous signals from speech via a new(More)
We report the results of investigations in acoustic modeling, language modeling and decoding techniques, for DARPA Communicator, a speaker-independent, telephone-based dialog system. By a combination of methods, including enlarging the acoustic model, augmenting the recognizer vocabulary, conditioning the language model upon dialog state, and applying a(More)