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AI MAGAZINE 2020年第2期41卷 22-35页

作者： Liberman, Mark Wayne, Charles Univ Penn Dept Linguist Philadelphia PA 19104 USA Univ Penn Dept Comp & Informat Sci 200 S 33Rd St Philadelphia PA 19104 USA

human language technology encompasses a wide array of speech and text processing capabilities. The Defense Advanced Research Projects Agency's pioneering research on automatic transcription, translation, and content analysis were major artificial intelligence success stories that changed science fiction into social fact. During a 40-year period, 10 seminal DARPA programs produced breakthrough capabilities that were further improved and widely deployed in popular consumer products, as well as in many commercial, industrial, and governmental applications. The Defense Advanced Research Projects Agency produced the core enabling technologies by setting crisp, aggressive, and quantitative technical objectives;by providing strong multiyear funding;and by using the Defense Advanced Research Projects Agency's Common Task Method, which was powerful, efficient, and easy to administer. To achieve these breakthroughs, multidisciplinary academic and industrial research teams working in parallel took advantage of increasingly large and diverse sets of linguistic data and rapidly increasing computational power to develop and use increasingly sophisticated forms of machine learning. This article describes the progression of technical advances underlying key successes and the seminal programs that produced them.

关键词： human language technology Translation language Artificial intelligence technology Content analysis language technology human

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human language technology and its role in information access and management

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Cataloging and Classification Quarterly 2003年第1-2期37卷 131-151页

作者： Hadi, Widad Mustafa el UFR IDST and CERSATES (CNRS UMR 8529) Université Charles De Gaulle Villeneuve D'Ascq F-59653 Lille 3 BP 149 France

The role of linguistics in information access,1 extraction and dissemination is essential. Radical changes in the techniques of information and communication at the end of the twentieth century have had a significant ... 详细信息

The role of linguistics in information access,¹ extraction and dissemination is essential. Radical changes in the techniques of information and communication at the end of the twentieth century have had a significant effect on the function of the linguistic paradigm and its applications in all forms of communication. The introduction of new technical means have deeply changed the possibilities for the distribution of information. In this situation, what is the role of the linguistic paradigm and its practical applications, i.e., natural language processing (NLP) techniques when applied to information access? What solutions can linguistics offer in human computer interaction, extraction and management? Many fields show the relevance of the linguistic paradigm through the various technologies that require NLP, such as document and message understanding, information detection, extraction, and retrieval, question and answer, cross-language information retrieval (CLIR), text summarization, filtering, and spoken document retrieval. This paper focuses on the central role of human language technologies in the information society, surveys the current situation, describes the benefits of the above mentioned applications, outlines successes and challenges, and discusses solutions. It reviews the resources and means needed to advance information access and dissemination across language boundaries in the twenty-first century. Multilingualism, which is a natural result of globalization, requires more effort in the direction of language technology. The scope of human language technology (HLT) is large, so we limit our review to applications that involve multilinguality. © 2003 by The Haworth Press, Inc. All rights reserved.

关键词： human language technology Multilinguality Natural language processing

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human language technology Audit 2018: Design Considerations and Methodology

Human Language Technology Audit 2018: Design Considerations ...

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International Conference on Intelligent & Innovative Computing Applications (ICONIC)

作者： Wilken, Ilana Moors, Carmen Gumede, Tebogo Calteaux, Karen CSIR Meraka Inst Human Language Technol Res Grp Pretoria South Africa

ISBN: (纸本)9781538664773

technology audits can play a significant role in surfacing information which can be used by researchers, policy-makers and funders alike to build a country's research and development system of innovation towards increasing its competitiveness, contributing to its economy and bridging the digital divide. In 2016, South Africa established a Centre for Digital language Resources (SADiLaR) with the aim of supporting a large research infrastructure programme tasked with bringing South African language resources into the digital age. This paper discusses the design considerations and methodology employed to undertake one of the first projects funded by SADiLaR: an updated audit of human language technology resources in South Africa. The paper aims to provide sufficient information to replicate such a technology audit in other environments. The design considerations aim to ensure a pleasant user experience, in order to facilitate as much input as possible. The approach aims to ensure that a sustainable audit tool is developed which can be hosted by SADiLaR in future.

关键词： human language technology technology audit language resources text resources speech resources digital humanities

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human language technology Audit 2018: Analysing the development trends in resource availability in all South African languages

Human Language Technology Audit 2018: Analysing the developm...

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Annual Conference of the South-African-Institute-of-Computer-Scientists-and-Information-Technologists (SAICSIT)

作者： Moors, Carmen Wilken, Ilana Calteaux, Karen Gumede, Tebogo CSIR Meraka Inst Human Language Technol Res Grp Pretoria South Africa

ISBN: (纸本)9781450366472

Almost a decade has passed since the first audit on the state of HLT in South Africa was published in 2009. An increase in HLT R&D in South Africa since then, as well as developments in language resource management in the country surfaced the need for an updated audit of HLT resources. Consolidating information on the availability and maturity of HLT resources provides valuable information for both researchers and decision-makers. On the one hand, information on available HLT resources enables researchers to identify new opportunities for multidisciplinary research. On the other, decision-makers can use the information to determine priorities for resource development and where to focus their investments. The paper presents an overview of the main findings of an audit of HLT resources, undertaken in 2017/8, and makes some suggestions for ensuring that the current information is continually updated as new resources are developed.

关键词： human language technology technology audit language resources Text resources Speech resources Digital humanities

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The South African human language technology Audit

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language RESOURCES AND EVALUATION 2011年第3期45卷 271-288页

作者： Grover, Aditi Sharma van Huyssteen, Gerhard B. Pretorius, Marthinus W. CSIR Human Language Technol Res Grp Meraka Inst ZA-0001 Pretoria South Africa Univ Pretoria Grad Sch Technol Management ZA-0002 Pretoria South Africa North West Univ Ctr Text Technol CTexT Potchefstroom South Africa

human language technology (HLT) has been identified as a priority area by the South African government. However, despite efforts by government and the research and development (R&D) community, South Africa has not yet been able to maximise the opportunities of HLT and create a thriving HLT industry. One of the key challenges is the fact that there is insufficient codified knowledge about the current South African HLT components, their attributes and existing relationships. Hence a technology audit was conducted for the South African HLT landscape, to create a systematic and detailed inventory of the status of the HLT components across the eleven official languages. Based on the Basic language Resource Kit (BLaRK) framework Krauwer (ELRA Newslett 3(2), 1998), we used various data collection methods (such as focus groups, questionnaires and personal consultations with HLT experts) to gather detailed information. The South African HLT landscape is analysed using a number of complementary approaches and based on the interpretations of the results, recommendations are made on how to accelerate HLT development in South Africa, as well as on how to conduct similar audits in other countries and contexts.

关键词： technology audit human language technology language resources BLaRK language audit language resource infrastructure Resource-scarce languages

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Better Textbooks with human language technology 18

Better Textbooks with Human Language Technology

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41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

作者： Das, Sudeshna Indian Inst Technol Kharagpur W Bengal India

ISBN: (纸本)9781450356572

Almost every part of the world relies on textbooks as the primary medium of imparting education. The quality of education, thus, is correlated with the quality of textbooks. In general, the quality of content in the textbooks used in the less-developed countries of the world is not up to the mark [1]. In addition to their intended purpose of delivering information, textbooks also promote behaviours that adults wish to pass on to the next generation [7]. It is, thus, important to ensure that textbooks are helpful in effective learning and do not condone undesirable social mores. The task of evaluating textbooks against these parameters is not trivial: experts must go through the entire content manually. This exercise being not only laborious, but also expensive [3]. This thesis attempts to propose a feasible computational alternative to this processThe dataset that we are working with is comprised of school textbooks collected from different boards of education of two south-east Asian countries that are widely regarded as 'developing countries'[4]. In general, a digitized textbook throws a large number of computational problems that require ideas from a number of disciplines such as Natural language Processing, Information Retrieval, human Computer Interaction and Cognitive Science. In this thesis we focus on the following research questions. Research Question 1 How can we automatically identify the text fragments that reflect gender bias from textbooks?The prevalence of gender bias has been reported in textbooks from many parts of the world [5,6]. Computational efforts to contain the effects of such biases have been proposed [2], but the detection of presence of gender bias, and identifying text passages that exhibit such biases is an unexplored problem. We model the task as a binary classification problem, with one class being biased text, and the other being unbiased text. For classifying text fragments, we propose a boosted memory-based model to learn the hidden

关键词： Textbooks human language technology Web resource mining

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Decision support for detecting sensitive text in government records

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ARTIFICIAL INTELLIGENCE AND LAW 2025年第1期33卷 171-197页

作者： Branting, Karl Brown, Bradford Giannella, Chris Guilder, James Van Harrold, Jeff Howell, Sarah Baron, Jason R. Mitre Corp Mclean VA 22102 USA Univ Maryland College Pk MD USA

Freedom of information laws promote transparency by permitting individuals and organizations to obtain government documents. However, exemptions from disclosure are necessary to protect privacy and to permit government officials to deliberate freely. Deliberative language is often the most challenging and burdensome exemption to detect, leading to high processing costs and delays in responding to open-records requests. This paper describes a novel deliberative-language detection model trained on a new annotated training set. The deliberative-language detection model is a component of a decision-support system for open-records requests under the US Freedom of Information Act, the FOIA Assistant, that ingests documents responsive to an open-records requests, suggests passages likely to be subject to deliberative language, privacy, or other exemptions, and assists analysts in rapidly redacting suggested passages. The tool's interface is based on extensive human-factors and usability studies with analysts and is currently in operational testing by multiple US federal agencies.

关键词： Artificial intelligence and law Freedom of information law Machine learning human language technology human factors analysis human-computer interface

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Scalable and explainable legal prediction

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ARTIFICIAL INTELLIGENCE AND LAW 2021年第2期29卷 213-238页

作者： Branting, L. Karl Pfeifer, Craig Brown, Bradford Ferro, Lisa Aberdeen, John Weiss, Brandy Pfaff, Mark Liao, Bill Mitre Corp Mclean VA 22102 USA MITRE Corp Ann Arbor MI USA Mitre Corp Burlington Rd Bedford MA 01730 USA

Legal decision-support systems have the potential to improve access to justice, administrative efficiency, and judicial consistency, but broad adoption of such systems is contingent on development of technologies with low knowledge-engineering, validation, and maintenance costs. This paper describes two approaches to an important form of legal decision support-explainable outcome prediction-that obviate both annotation of an entire decision corpus and manual processing of new cases. The first approach, which uses an attention network for prediction and attention weights to highlight salient case text, was shown to be capable of predicting decisions, but attention-weight-based text highlighting did not demonstrably improve human decision speed or accuracy in an evaluation with 61 human subjects. The second approach, termed semi-supervised case annotation for legal explanations, exploits structural and semantic regularities in case corpora to identify textual patterns that have both predictable relationships to case decisions and explanatory value.

关键词： Artificial intelligence and law Machine learning human language technology Explainable prediction

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Updated MINDS Report on Speech Recognition and Understanding, Part 2

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IEEE SIGNAL PROCESSING MAGAZINE 2009年第4期26卷 78-85页

作者： Baker, Janet M. Deng, Li Khudanpur, Sanjeev Lee, Chin-Hui Glass, James R. Morgan, Nelson O'Shaughnessy, Douglas Saras Inst W Newton MA USA Univ Washington Seattle WA 98195 USA Microsoft Res Redmond WA USA Johns Hopkins Univ GWC Whiting Sch Engn Baltimore MD USA Georgia Inst Technol Sch ECE Atlanta GA 30332 USA Bell Labs Murray Hill NJ 07974 USA MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA Univ Calif Berkeley ICSI Res Lab Berkeley CA 94720 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Univ Quebec INRS EMT Ste Foy PQ G1V 2M3 Canada

This article is the second part of an updated version of the "MINDS 2006-2007 Report of the Speech Understanding Working Group," one of five reports emanating from two workshops entitled "Meeting of the MINDS: Future Directions for human language technology," sponsored by the U.S. Disruptive technology Office (DTO). (MINDS is an acronym for "machine translation, information retrieval, natural-language processing, data resources, and speech understanding").

关键词： information retrieval language translation natural language processing speech recognition MINDS data resources human language technology machine translation natural-language processing speech understanding interpreters Mind information retrieval Natural language Processing speech understanding

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Spoken language understanding

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IEEE SIGNAL PROCESSING MAGAZINE 2005年第5期22卷 16-31页

作者： Wang, YY Deng, L Acero, A IEEE the Acoustical Society of America

This article is intended to serve as an introduction to the field of statistical SLU, based on the mainstream statistical modeling approach that shares a similar mathematical framework with many other statistical pattern recognition applications such as speech recognition. In particular, we formulated a number of statistical models for SLU in the literature as extensions to HMMs as segment models, where a multiple-word block (segment) with word dependency is generated from each underlying Markov state corresponding to each individual semantic slot defined from the application domain. In the past, due partly to its nature of symbolic rather than numeric processing, the important field of SLU in human language technology has not been widely exposed to the signal processing research community. However, many key techniques in SLU originated from statistical signal processing. And because SLU is becoming increasingly important, as one major target application area of ASR that has been dear to many signal processing researchers, we contribute this article to provide a natural bridge between ASR and SLU in methodological and mathematical foundation. It is our hope that when the mathematical basis of SLU becomes well known through this introductory article, more powerful techniques established by signal processing researchers may further advance SLU to form a solid application area, making speech technology a successful component for intelligent human-machine communication.

关键词： hidden Markov models speech recognition statistical analysis human language technology intelligent human-machine communication multiple-word block segment models speech technology spoken language understanding stat signal processing program area Statistical analysis spoken language understanding Hidden Markov models Statistical methods statistical models (nuclear)

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