OOV

As for the OOV problem , the thesis adopts character based method .

针对日文分词中的未登录词问题，提出基于字的识别方法。

Research on Web Based Translation Mining of OOV in Cross-Language Information Retrieval System

基于网络的跨语言信息检索中OOV译文挖掘研究

Study on Chinese OOV Identification Based on Extension Professional Search Engine Unknown Word of Recognition

基于统计信息的未登录词的扩展识别方法对专业搜索引擎中未登录词的识别研究

The translation of OOV terms is facing new challenges .

未登录词的翻译面临着新的挑战。

OOV is a common problem in small grammars .

OOV是小文法中的一个常见问题。

Word Pair Extraction and Web-based Mining of OOV Translations

词对抽取及基于网络的未登录词译文挖掘

This proposal uses the weight attribute to deal with OOV and the tag element to handle context .

此提议使用weight属性来处理OOV和tag元素，以处理上下文。

The experimental results show that this algorithm is very simple and efficient , which attains over 80 % OOV rejection rate .

实验结果表明，该算法计算简单，实时性好，且效果显著，拒识率达80%以上。

The most of approach is based on the concept with stopwords interference with recognition of OOV word .

以往大多方法基于停用词干扰未登录词识别这一理念，将其去除后再进行处理。

In practical automatic speech recognition systems , out-of-vocabulary ( OOV ) utterance detection and rejection represent an important part .

在自动语音识别系统的实际应用中，词表外（Out-of-Vocabulary，OOV）语音的检测与拒识非常重要。

Dialog managers are important in their own right because they offer ways to deal with issues such as intelligent response and OOV recognition .

对话管理器很重要，因为它们提供处理智能响应和OOV识别等问题的方式。

This paper proposes a new OOV rejection algorithm based on support vector machine and uses it in isolated-word speech recognition system based on DSP hardware environment .

针对语音识别的实时性要求，提出了一种新的基于支持向量机的OOV快速拒识算法，并将其应用于基于DSP实现的孤立词语音识别系统中。

Search engine based method utilizes the high OOV translation inclusion rate feature of search engine to mine the translation of OOV for query translation .

基于搜索引擎的查询翻译方法利用了搜索引擎OOV译文高资源覆盖度的特点，从搜索引擎挖掘译文用于查询翻译。

Looking at the Balance between the Identified IV and OOV from the ACL & SIGHAN International Participle Competition

从ACL-SIGHAN国际分词竞赛看已知词和未登录词识别的平衡问题

To solve these two problems , we first deeply analyze the problems and then put forward the homologous strategy of solution . ( 1 ) Web-based OOV translation extraction .

针对这两个问题，本文给出了相应的解决策略：（1）基于Web的未登录词翻译提取。

This model that considering corpus information and context information can improves the quality of segmentation . ( 2 ) Recognition of OOV word based on stopwords ( ROWS ) is proposed .

理论分析及实验表明综合考虑语料信息和语境信息可有效提高分词的质量。（2）提出一种基于停用词驱动的未登录词识别方法ROWS。

Due to the appearance of new Out-of-Vocabulary terms , the accuracy of the OOV term translation has been affected by scarcity of the corpus in traditional OOV term translation methods .

由于新的未登录词的不断出现，传统的未登录词方法中，也因为语料库稀缺等问题而影响翻译的准确率。

The better performance of OOV recognition the higher accuracy of the segmentation system in whole , and the accuracy of statistic segmentation systems with character-based tagging approach outperforms any other word-based system .

实验证明，能够大幅度提高未登录词识别性能的字标注统计学习方法优于以往的基于词（或词典）的方法，并使自动分词系统的精度达到了新高。

The previous methods mainly used the bilingual corpus as the resource ; but these methods are limited on scale and diversity , and also can not handle the out of vocabulary ( OOV ) problem well .

早期的方法主要是从平行语料中进行抽取，这类方法存在规模不足、领域局限、不能很好的处理新词等问题。

According to the characteristics of web text , we focused on the Out-of-Vocabulary ( OOV ) word identification problem in Chinese word segmentation task , as well as the disambiguation and the ability to deal with huge amount of text .

根据web文本环境的特点，研究重点在于中文分词中的未登录词识别问题，同时兼顾切分歧义消解、整体切分准确率和高效处理海量文本的能力。

As for the OOV problem in dictionary based method , the thesis adopts transliteration method for Japanese person names , location names and Japanese katakana words , which did not exist in the Japanese-English dictionary , according to Japanese word characteristics .

针对基于词典的翻译方法中词典覆盖度的问题，本文根据日文的特点，采用对词典中不存在的日文人名、地名以及片假名词的音译方法，显著提高了查询翻译的效果。

This method first analyzes the translation feature of an OOV term , namely the identification of translation OOV , transliteration OOV and mix-translation OOV , and then the identification result is used in the follow procedures of candidate translation extraction and selection .

该方法首先对未登录词的翻译特征进行分析，即意译未登录词、音译未登录词和合译未登录词的判别，并将判别结果应用于后续的候选翻译词抽取和选择。

After the experiment , we found that the accuracy of Ranking SVM was slightly higher than the SVM . Finally , the experiments based on person names , location names and organization names in English-Chinese and Chinese-English OOV term translation are executed , and obtain well translation accuracy .

经过实验，发现RankingSVM的准确率略高于SVM。最后，分别通过对英汉和汉英翻译中的人名、地名、组织机构名三类未登录词进行实验，取得了较好的翻译准确率。

To deal with the OOV words , we proposed POC-NLW character tagging templates to represent the word-internal component mechanism in Chinese words on the character-level , which were combined into the Hidden Markov model to implement the Chinese word segmentation task as a character sequence tagging procedure .

在未登录词识别方面，提出了POC-NLW字符标记模板，从字符级别的粒度来表征中文词汇的构成机制，并结合隐马尔可夫模型，实现了基于字符序列标注的中文分词方法。