## LANGUAGE MODEL ADAPTATION FOR AUTOMATIC SPEECH RECOGNITION AND STATISTICAL MACHINE TRANSLATION (2004)

Citations: | 1 - 0 self |

### BibTeX

@MISC{Kim04languagemodel,

author = {Woosung Kim},

title = {LANGUAGE MODEL ADAPTATION FOR AUTOMATIC SPEECH RECOGNITION AND STATISTICAL MACHINE TRANSLATION},

year = {2004}

}

### OpenURL

### Abstract

Language modeling is critical and indispensable for many natural language ap-plications such as automatic speech recognition and machine translation. Due to the complexity of natural language grammars, it is almost impossible to construct language models by a set of linguistic rules; therefore statistical techniques have been dominant for language modeling over the last few decades. All statistical modeling techniques, in principle, work under some conditions: 1) a reasonable amount of training data is available and 2) the training data comes from the same population as the test data to which we want to apply our model. Based on observations from the training data, we build statistical models and therefore, the success of a statistical model is crucially dependent on the training data. In other words, if we don’t have enough data for training, or the training data is not matched with the test data, we are not able to build accurate statistical models. This thesis presents novel methods to cope with those problems in language modeling—language model adaptation.

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Citation Context ...Method: Maximum Entropy Model There has been considerable research for combining topic related information with N-gram models (Bellegarda, 1998; Clarkson and Robinson, 1997; Iyer and Ostendorf, 1999; =-=Kneser et al., 1997-=-). The basic idea of these approaches is to exploit the differences of word N-gram distributions across topics. That is, first the whole training data is separated into several topic-specific clusters... |

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Citation Context ...ea to use bootstrap resampling for measuring confidence intervals for MT scores was originally proposed by Franz Och. This was in fact adapted from the method to measure confidence intervals for ASR (=-=Bisani and Ney, 2004-=-). 4 Notice that multiple references are typically available for one segment. 111sRemark: This bootstrap estimate has been implemented by Och et al. (2003) and we use this implementation in our analys... |

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Citation Context ...d they are difficult to quantify. Therefore, the automatic evaluation of SMT outputs has been an important issue, and still there is no single standard measure (Akiba et al., 2001; Lin and Och, 2004; =-=Melamed et al., 2003-=-; NIST, 2002; Papineni et al., 2002). The main difficulty in the automatic evaluation of SMT lies in the fact that there is no single ground truth. In other words, there may be many correct translatio... |

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Citation Context ...d a classical task of CLIR, which selects similar or relevant documents for a given query where the documents and the query are written in different languages and it has been long and widely studied (=-=Davis and Ogden, 1997-=-; Grefenstette and Grefenstette, 1998; Oard, 1997). In our approach, we don’t necessarily use the state-of-the-art IR method; rather, we use a simple and crude IR method, vector space model, and we tr... |

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Citation Context ...NN Headline News CCTV ABC World News Tonight CTS NBC Nightly News CBS-Taiwan MSNBC News with Brian Williams 1.2 Related Work: Topic Detection and Tracking The topic detection and tracking (TDT) task (=-=Christopher et al., 2000-=-) is a concrete example of a large publicly funded technology demonstration program which motivates the research described in this dissertation. The original TDT corpus contains news broadcasts from 4... |

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Citation Context ... an example of the significance test: a matched pairs sentencesegment word error (MAPSSWE) test, which can be performed by a NIST (National Institute of Standards and Technology) ASR evaluation tool (=-=Pallett et al., 1990-=-). Since we are interested in whether one system performs significantly better than the other, our hypotheses would be given by: H0 : the mean of error differences between two systems is zero, Ha : th... |

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Citation Context ...s, but human judgments are expensive and they are difficult to quantify. Therefore, the automatic evaluation of SMT outputs has been an important issue, and still there is no single standard measure (=-=Akiba et al., 2001-=-; Lin and Och, 2004; Melamed et al., 2003; NIST, 2002; Papineni et al., 2002). The main difficulty in the automatic evaluation of SMT lies in the fact that there is no single ground truth. In other wo... |

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