NYU language modeling experiment for 1996 CSR evaluation
Satoshi Sekine, Andrew Borthwick, Ralph Grishman · 1997
This paper describes NYU’s effort toward improving recognition accuracy for the 1996 ARPA Large Vocabulary Continuous Speech Recognition evaluation. We are trying to develop different kinds of language models including longer-range models and a linguistically motivated model. For the system described here, we used as a starting point the scores produced by SRI’s acoustic and language models. These are linearly combined with the scores produced by the NYU language models. This paper also describes some experiments we tried which were not used in the official experiment, including experiments with perplexity minimization, Maximum Entropy modeling and parsing.