Noisy channel model

Xem 1-11 trên 11 kết quả Noisy channel model
  • Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased performance. Current correction techniques mainly focus on identifying and correcting a specific type of error, such as verb form misuse or preposition misuse, which restricts the corrections to a limited scope. We introduce a novel technique, based on a noisy channel model, which can utilize the whole sentence context to determine proper corrections.

    pdf11p hongdo_1 12-04-2013 35 2   Download

  • This paper describes a noisy channel model of speech repairs, which can identify and correct repairs in speech transcripts. A syntactic parser is used as the source model, and a novel type of TAG-based transducer is the channel model. The use of TAG is motivated by the intuition that the reparandum is a “rough copy” of the repair. The model is trained and tested on the Switchboard disfluency-annotated corpus.

    pdf8p bunbo_1 17-04-2013 29 2   Download

  • We present a document compression system that uses a hierarchical noisy-channel model of text production. Our compression system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. The system then uses a statistical hierarchical model of text production in order to drop non-important syntactic and discourse constituents so as to generate coherent, grammatical document compressions of arbitrary length.

    pdf8p bunmoc_1 20-04-2013 30 1   Download

  • The noisy channel model has been applied to a wide range of problems, including spelling correction. These models consist of two components: a source model and a channel model. Very little research has gone into improving the channel model for spelling correction. This paper describes a new channel model for spelling correction, based on generic string to string edits. Using this model gives significant performance improvements compared to previously proposed models.

    pdf8p bunrieu_1 18-04-2013 41 1   Download

  • We introduce a probabilistic noisychannel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outperforms a stateof-the-art rule-based QA system that uses similar resources. We also show that the model we propose is flexible enough to accommodate within one mathematical framework many QA-specific resources and techniques, which range from the exploitation of WordNet, structured, and semi-structured databases to reasoning, and paraphrasing.

    pdf8p bunbo_1 17-04-2013 33 2   Download

  • This paper presents a method for incorporating word pronunciation information in a noisy channel model for spelling correction. The proposed method builds an explicit error model for word pronunciations. By modeling pronunciation similarities between words we achieve a substantial performance improvement over the previous best performing models for spelling correction.

    pdf8p bunmoc_1 20-04-2013 23 2   Download

  • This paper presents noisy-channel based Korean preprocessor system, which corrects word spacing and typographical errors. The proposed algorithm corrects both errors simultaneously. Using Eojeol transition pattern dictionary and statistical data such as Eumjeol n-gram and Jaso transition probabilities, the algorithm minimizes the usage of huge word dictionaries.

    pdf4p hongvang_1 16-04-2013 30 1   Download

  • In Statistics-Based Summarization - Step One: Sentence Compression, Knight and Marcu (Knight and Marcu, 2000) (K&M) present a noisy-channel model for sentence compression. The main difficulty in using this method is the lack of data; Knight and Marcu use a corpus of 1035 training sentences. More data is not easily available, so in addition to improving the original K&M noisy-channel model, we create unsupervised and semi-supervised models of the task.

    pdf8p bunbo_1 17-04-2013 29 3   Download

  • The noisy channel model approach is successfully applied to various natural language processing tasks. Currently the main research focus of this approach is adaptation methods, how to capture characteristics of words and expressions in a target domain given example sentences in that domain. As a solution we describe a method enlarging the vocabulary of a language model to an almost infinite size and capturing their context information.

    pdf8p hongvang_1 16-04-2013 29 2   Download

  • A statistical machine translation system based on the noisy channel model consists of three components: a language model (LM), a translation model (TM), and a decoder. For a system which translates from to English , the LM gives a foreign language a prior probability P and the TM gives a channel translation probability P . These models are automatically trained using monolingual (for the LM) and bilingual (for the TM) corpora.

    pdf8p bunmoc_1 20-04-2013 27 2   Download

  • IMPULSIVE NOISE 12.1 12.2 12.3 12.4 12.5 12.6 12.7 Impulsive Noise Statistical Models for Impulsive Noise Median Filters Impulsive Noise Removal Using Linear Prediction Models Robust Parameter Estimation Restoration of Archived Gramophone Records Summary I mpulsive noise consists of relatively short duration “on/off” noise pulses, caused by a variety of sources, such as switching noise, adverse channel environments in a communication system, dropouts or surface degradation of audio recordings, clicks from computer keyboards, etc.

    pdf23p khinhkha 30-07-2010 66 5   Download



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