Обучение на основе преобразований

Eric Brill introduced transformation-based learning and showed that it can do part-of- speech tagging with fairly high accuracy. The same method can be applied at a higher level of textual …...

The #u-TBL system represents an attempt to use the search and database capabilities of the Prolog pro- gramming language to implement a generalized form of transformation-based learning. In the true …...

Transformation-based learning has been success- fully employed to solve many natural language processing problems. It has many positive fea- tures, but one drawback is that it does not provide estimates …...

Information extraction (IE) systems are costly to build because they require development texts, pars- ing tools, and specialized dictionaries for each ap- plication domain and each natural language that needs …...

This paper presents a classifier-combination experimental framework for named entity recognition in which four diverse classi- fiers (robust linear classifier, maximum en- tropy, transformation-based learning, and hid- den Markov model) …...

This paper presents a Chinese word segmen- tation system which can adapt to different domains and standards. We first present a sta- tistical framework where domain-specific words are identified in …...

The regular occurrence of disfluencies is a distinguishing characteristic of spontaneous speech. Detecting and removing such disflu- encies can substantially improve the usefulness of spontaneous speech transcripts. This pa- per …...

Recognition errors hinder the prolifera- tion of speech recognition (SR) systems. Based on the observation that recogni- tion errors may result in ungrammatical sentences, especially in dictation appli- cation where …...

We propose a conditional random field- based method for supertagging, and ap- ply it to the task of learning new lexi- cal items for HPSG-based precision gram- mars of English …...

. In this paper, we propose a Transformation-Based Learning (TBL) method on generating the Korean standard pronunciation. Previous studies on the phonological processing have been focused on the phonological rule …...

Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learn- ing (TBL). In this work, we apply …...

Although a lot of progress has been made recently in word segmentation and POS tagging for Chinese, the output of cur- rent state-of-the-art systems is too inaccu- rate to allow …...

We describe a transformation-based learning method for learning a sequence of mono- lingual tree transformations that improve the agreement between constituent trees and word alignments in bilingual corpora. Using the …...