| H93-1016 | fundamentally different from traditional | stochastic language modeling | . Firstly , conventional language |
| H92-1021 | presented two attempts to improve our | stochastic language modeling | . In the first , we identified |
| H92-1021 | attempts at improving our current | stochastic language modeling | techniques . In the first , we |
| H92-1019 | Stochastic Modeling Improvements in | stochastic language modeling | can be obtained by using adaptive |
| P98-2148 | always be the best in terms of | stochastic language modeling | . This is experimentally attested |
| P98-1047 | Abstract In this paper , we present a | stochastic language modeling | tool which aims at retrieving |
| N04-1039 | structuring probabilistic dependences in | stochastic language modeling | . Computer , Speech , and Language |
| N03-1001 | loop ) were constructed using the | stochastic language modeling | technique described by Riccardi |
| C00-1081 | stochastic parsers . 1 Introduction The | stochastic language modeling | , imported fl : om the speech |
| W98-1122 | probabilities in the context of | stochastic language modeling | for speech recognition and under |
| W98-1122 | , the goal of large vocabulary | stochastic language modeling | for speech recognition and understanding |
| P98-2148 | as we know . The methodology of | stochastic language modeling | , how - ever , allows us to separate |
| P98-2148 | Introduction An effectiveness of | stochastic language modeling | as a methodology of natural language |
| P99-1002 | words are very important issues . | Stochastic language modeling | , such as bigrams and trigrams |
| H92-1021 | Roukos <title> IMPROVEMENTS IN | STOCHASTIC LANGUAGE MODELING | </title> Ronald Rosenfeld Xuedong |
| W00-0508 | Translation Models Our approach to | stochastic language modeling | is based on the Variable Ngram |
| H92-1021 | Xuedong Huang IMPROVEMENTS IN | STOCHASTIC LANGUAGE MODELING | 1 . INTRODUCTION Linguistic constraints |
| W98-1238 | intractable . Recent advances in | stochastic language modeling | , however , have made it possible |
| H92-1010 | collaboration with researchers using | stochastic language modeling | based on grammatical categories |
| W96-0100 | <title> A Re-estimation Method for | Stochastic Language Modeling | from Ambiguous Observations Mikio |
