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A Noisy Channel Model Framework for Grammatical Correction
... The channel model provides a definition of trans- formations that could have been applied to a sen- tence before we observed ...the channel as one that sometimes replaces a word with one of the ... See full document
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A Noisy Channel Approach to Error Correction in Spoken Referring Expressions
... Shallow semantic parsers for SDSs have been used in (Coppola et al., 2009; Geertzen, 2009). Coppola et al. (2009) used FrameNet (Baker et al., 1998) to detect and filter the frames for tar- get words, and employed a ... See full document
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Learning a Spelling Error Model from Search Query Logs
... language model and probabilistic error model directly from search query logs without requiring a corpus of misspelled words paired with their ...spelling correction is analyzed, and an implementation ... See full document
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A Discriminative Model for Query Spelling Correction with Latent Structural SVM
... spelling correction with a discriminative ...discriminative model which naturally incorporates search in the learning ...the noisy channel model and can thus serve as a superior method ... See full document
11
CMUQ@QALB 2014: An SMT based System for Automatic Arabic Error Correction
... error model by analyzing error types and by creating an edit distance ...spelling correction of Arabic ...a Noisy Channel Model on word-based unigrams to detect and correct spelling ... See full document
6
A Noisy Channel Model for Document Compression
... hierarchical noisy-channel model of text ...hierarchical model of text produc- tion in order to drop non-important syn- tactic and discourse constituents so as to generate coherent, ... See full document
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Automated Whole Sentence Grammar Correction Using a Noisy Channel Model
... grammar correction tasks are often manually evaluated for each output cor- rection, or evaluated by taking a set of proper sen- tences, artificially introducing some error, and see- ing how well the algorithm ... See full document
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A Generative Probabilistic OCR Model for NLP Applications
... (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transforma- tion into the noisy output of an OCR ... See full document
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Chinese Spell Checking Based on Noisy Channel Model
... a channel model and a character- based language model in the noisy channel ...the channel probabilities for each charac- ter based on ngrams in Web ...generates correction ... See full document
8
An Improved Error Model for Noisy Channel Spelling Correction
... The above example points to advantages of our model compared to previous models based on weighted Damerau-Levenshtein distance. Note that neither P(f | ph) nor P(le | al) are modeled directly in the previous ... See full document
8
Noisy Channel for Low Resource Grammatical Error Correction
... on Grammatical Error Correction ...the noisy channel by combining a chan- nel model and language ...BERT model, which we fine-tune for specific error types and 2) OpenAI’s GPT-2 ... See full document
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A Framework for Spelling Correction in Persian Language Using Noisy Channel Model
... spelling correction in Farsi (Persian) ...powerful framework has been implemented because of lack of a large training set in Farsi as an accurate ...related correction string pairs have been obtained ... See full document
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A Spelling Correction Program Based on a Noisy Channel Model
... A Spelling Correction Program Based on a Noisy Channel Model 1 A Spelling Correction P r o g r a m Based on a N o i s y Channel M o d e l Mark D Kemighan Kenneth W Church William A Gale A T & T Bell L[.] ... See full document
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Grammatical Error Detection and Correction using a Single Maximum Entropy Model
... In contrast, we follow the work in (Jia et al., 2013a; Zhao et al., 2009a), integrating everything into one model. This integrated system holds a merit that a one-way feature selection benefits the whole system ... See full document
9
Analyzing Probability Vectors for Named Entity Statistical Machine Transliteration
... A conditional random field is defined as an undirected graphical model, or Markov random field, globally conditioned on X, the random variable representing observation sequences. Formally, definition of CRF is ... See full document
7
Minimally Augmented Grammatical Error Correction
... is model-independent and only requires clean monolingual data and potentially an available spell-checker ...guage model (LM) based approaches (Bryant and Briscoe, 2018; Stahlberg et ... See full document
7
Cross Sentence Grammatical Error Correction
... We also analyze the output words that produce at- tention distributions on the auxiliary context that deviate the most from a uniform distribution, indi- cating their dependence on cross-sentence context. For each output ... See full document
11
The Noisy Channel Model for Unsupervised Word Sense Disambiguation
... A note on the term “unsupervised” may be appropriate here. In the WSD literature “unsupervised” is typically used to describe systems that do not directly use sense- tagged corpora for training. However, many of these ... See full document
18
A TAG based noisy channel model of speech repairs
... The model is trained from the disfluency and POS tagged Switchboard corpus on the LDC Penn tree bank III CD-ROM (specifically, the files under dysfl/dps/swbd ... See full document
8
Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model
... LSTM noisy channel model outperforms the ...language model trained on Switch- board corpus results in the greatest ...the model can more easily detect the unexpected word order as- ... See full document
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