Multi-D Kneser-Ney Smoothing Preserving the Original Marginal Distributions
Smoothing is an essential tool in many NLP tasks, therefore numerous techniques have been developed for this purpose in the past. One of the most widely used smoothing methods are the Kneser-Ney smoothing (KNS) and its variants, including the Modified Kneser-Ney smoothing (MKNS), which are widely considered to be among the best smoothing methods available. Although when creating the original KNS the intention of the authors was to develop such a smoothing method that preserves the marginal distributions of the original model, this property was not maintained when developing the MKNS. In this article I would like to overcome this and propose such a refined version of the MKNS that preserves these marginal distributions while keeping the advantages of both previous versions. Beside its advantageous properties, this novel smoothing method is shown to achieve about the same results as the MKNS in a standard language modelling task.
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModellingSimilar Papers 제목 키워드 기반
Comparison of Modified Kneser-Ney and Witten-Bell Smoothing Techniques in Statistical Language Model of Bahasa Indonesia
Smoothing is one technique to overcome data sparsity in statistical language model. Although in its mathematical definition there is no explicit dependency upon specific natural language, different natures of natural lan…
Language ModelingLanguage ModellingN-gram Counts and Language Models from the Common Crawl
We contribute 5-gram counts and language models trained on the Common Crawl corpus, a collection over 9 billion web pages. This release improves upon the Google n-gram counts in two key ways: the inclusion of low-count e…
Language ModelingLanguage ModellingMachine TranslationSpeech RecognitionKneser-Ney Smoothing on Expected Counts
Richer Interpolative Smoothing Based on Modified Kneser-Ney Language Modeling
A Generalized Language Model as the Combination of Skipped n-grams and Modified Kneser-Ney Smoothing
We introduce a novel approach for building language models based on a systematic, recursive exploration of skip n-gram models which are interpolated using modified Kneser-Ney smoothing. Our approach generalizes language …
Language ModelingLanguage Modelling