کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
410604 679154 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improving a statistical language model through non-linear prediction
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Improving a statistical language model through non-linear prediction
چکیده انگلیسی

We show how to improve a state-of-the-art neural network language model that converts the previous “context” words into feature vectors and combines these feature vectors linearly to predict the feature vector of the next word. Significant improvements in predictive accuracy are achieved by using a non-linear subnetwork to modulate the effects of the context words or to produce a non-linear correction term when predicting the feature vector. A log-bilinear language model that incorporates both of these improvements achieves a 26% reduction in perplexity over the best n-gram model on a fairly large dataset.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 72, Issues 7–9, March 2009, Pages 1414–1418
نویسندگان
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