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1.
Patent databases are a counterpart of a technical encyclopedia providing a valuable informational source from patent documents. Patents apply to a wide variety of uses, and this is expanding. The increasing kinds of users of patent documents result in a lack of educational programs regarding this matter. This paper describes Patent2Net (P2N) a patentinformatic suite whose purpose is to fill the lack in the academic world (education and research) of a tool to use with students (STEM, Masters, PhD), by valuation services and for defining corpuses for research in general patent analysis, specifically on textual content. P2N is a free open-source modular, scalable, customizable and derivable tool, written in the python language. We present here the main functions of the tool and the technical aspects after discussing the skills to be reached by students for state of the art patent analysis.  相似文献   
2.
情感语音合成作为一个新兴的语音合成方向,糅合生理学、心理学、语言学和信息科学等各学科知识,可以应用于文本阅读、信息查询发布和计算机辅助教学等领域,能够很好地将语音的口语分析、情感分析与计算机技术有机融合,为实现以人为本,具有个性化特征的语音合成系统奠定基础。目前的情感语音合成工作可分为基于规则合成和基于波形拼接合成两类。情感语音合成研究分为情感分析和语音合成两个部分。其中.情感分析的主要工作是收集不同情感的语音数据、提取声学特征,分析声学特征与情感联系;语音合成的主要工作是建立情感转换模型,利用情感转换模型实现合成。  相似文献   
3.
While there is great potential for sign language animation generation software to improve the accessibility of information for deaf individuals with low written-language literacy, the understandability of current sign language animation systems is limited. Data-driven methodologies using annotated sign language corpora encoding detailed human movement have enabled some researchers to address several key linguistic challenges in ASL generation. This article motivates and describes our current research on collecting a motion-capture corpus of American Sign Language (ASL). As an evaluation of our motion-capture configuration, calibration, and recording protocol, we have conducted several rounds of evaluation studies with native ASL signers, and we have made use of our collected data to synthesize novel animations of ASL, which have also been evaluated in experimental studies with native signers.  相似文献   
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基于语料库和面向统计学的自然语言处理技术   总被引:15,自引:1,他引:14  
1引言 语料库语言学(Corpus Linguistics)是八十年代才崭露头角的一门新的计算语言学分支学科.它研究机器可读的自然语言文本的采集、存储、检索、统计、语法标注、句法语义分,以及具有上述功能的语料库在语言定量分析、词典编纂、作品风格分  相似文献   
6.
In this paper we focus our attention on the second step algorithms of the Burrows–Wheeler compression algorithm, which in the original version is the Move To Front transform. We discuss many of its replacements presented so far, and compare compression results obtained using these replacements. Then we propose a new algorithm that yields a better compression ratio than the previous algorithms. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   
7.
词义消歧一直是一个难点,同时,也是很多领域都需解决的一个环节。该文首先介绍了目前基于语料库进行词义消歧方法的研究进展和各自的特点,在此基础上探讨了一种基于实例和基于统计的方法(即基于语料库的两种主流方法)相结合的混合策略,并对其可能性和优越性进行了讨论。  相似文献   
8.
In this paper we describe a database that consists of handwritten English sentences. It is based on the Lancaster-Oslo/Bergen (LOB) corpus. This corpus is a collection of texts that comprise about one million word instances. The database includes 1,066 forms produced by approximately 400 different writers. A total of 82,227 word instances out of a vocabulary of 10,841 words occur in the collection. The database consists of full English sentences. It can serve as a basis for a variety of handwriting recognition tasks. However, it is expected that the database would be particularly useful for recognition tasks where linguistic knowledge beyond the lexicon level is used, because this knowledge can be automatically derived from the underlying corpus. The database also includes a few image-processing procedures for extracting the handwritten text from the forms and the segmentation of the text into lines and words. Received September 28, 2001 / Revised October 10, 2001  相似文献   
9.
汉语树库的构建   总被引:11,自引:7,他引:11  
本文讨论了汉语树库构建的若干基础问题, 包括一个适合于自动分析和人工标注的汉语句法标记集、汉语树库加工处理规范和人机互助的树库加工模型, 介绍了一个已经实现的汉语自动句法标注系统, 和在此基础上进行的一些树库构建实验, 最后提出了构建大规模汉语树库的设想。  相似文献   
10.
The Web is a source of valuable information, but the process of collecting, organizing, and effectively utilizing the resources it contains is difficult. We describe CorpusBuilder, an approach for automatically generating Web search queries for collecting documents matching a minority concept. The concept used for this paper is that of text documents belonging to a minority natural language on the Web. Individual documents are automatically labeled as relevant or nonrelevant using a language filter, and the feedback is used to learn what query lengths and inclusion/exclusion term-selection methods are helpful for finding previously unseen documents in the target language. Our system learns to select good query terms using a variety of term scoring methods. Using odds ratio scores calculated over the documents acquired was one of the most consistently accurate query-generation methods. To reduce the number of estimated parameters, we parameterize the query length using a Gamma distribution and present empirical results with learning methods that vary the time horizon used when learning from the results of past queries. We find that our system performs well whether we initialize it with a whole document or with a handful of words elicited from a user. Experiments applying the same approach to multiple languages are also presented showing that our approach generalizes well across several languages regardless of the initial conditions.  相似文献   
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