Spoken Language Processing by Minimum Total Penalty Dependency Analysis Method

本研究项目的成果可分为1.理论基础，2。文题切分和长句切分; 3.韵律信息的使用，以及4.句子压缩，所有相关的最低总刑罚的方法。从“最小费用分割问题”的角度研究了相关性分析。结果表明，各种依赖分析算法可以通过改变成本的定义。还明确指出，最小总惩罚法允许使用广泛的数字信息作为语言知识。在进行依存分析之前，有必要将一个句子分割成文节短语。在这项工作中，决策树方法被应用到这个问题，给出了更高的分割精度比传统的方法数据。决策树技术也被应用到长句的分割，这是依赖分析的预处理。结果表明，一组分割 ...更多信息 通过该方法自动获取规则.为了发现韵律特征中包含的句法信息，建立了韵律特征与短语间依存距离之间的统计模型。然后将该模型与最小总惩罚分析器结合，以衡量韵律信息对依存分析的有效性。暂停的持续时间被认为是非常有效的。需要进一步研究以利用与音调、力度和语速相关的韵律特征。4.针对在线电视字幕生成等应用，提出了一种有效的句子压缩算法。该算法从一个原始句子中选择一个最佳的文题子序列，使文题重要性分数和短语间依赖性分数之和最大化。未来的工作包括调查文题重要性分数和短语间依存分数的更好的定义。利用大量的测试数据来评价缩短句的质量也是必要的。少

Results of this research project can be classified into 1. theoretical basis, 2. bunsetsu segmentation and segmentation of long sentences, 3. use of prosodic information, and 4. sentence compaction, all related to the minimum total penalty method.1. Dependency analysis was investigated from a view point of "minimum cost segmentation problem". It was shown that various dependency analysis algorithms can be derived by changing the definition of the cost. It was also made clear that the minimum total penalty method allows the use of a wide range of numerical information as linguistic knowledge.2. It is necessary to segment a sentence into bunsetsu phrases prior to dependency analysis. In this work, a decision tree method was applied to this problem, giving higher segmentation accuracy than conventional methods data. The decision tree technique was also applied to segmentation of long sentences, which is pre-processing for dependency analysis. It was demonstrated that a set of segmentation … More rules was automatically acquired by this method.3. To find out syntactic information contained in prosodic features, a statistical model was created that represents a relationship between prosodic features and inter-phrase dependency distance. The model was then incorporated into the minimum total penalty parser to measure the effectiveness of prosodic information for dependency analysis. The duration of pause was found to be very effective. Further investigation is necessary to make use of prosodic features related to pitch, power, and speaking rate.4. An efficient sentence compaction algorithm was developed for such application as generation of on-line TV closed-captions. This algorithm selects an optimal bunsetsu subsequence from an original sentence that maximizes the sum of bunsetsu importance scores and inter-phrase dependency scores. Future work includes investigation of better definitions of bunsetsu importance score and inter-phrase dependency score. It is also necessary to evaluate the quality of shortened sentences using large amount of test data. Less