CI-P: Planning for Scalable Language Resource Creation through Novel Incentives and Crowdsourcing

CI-P：通过新颖的激励措施和众包规划可扩展的语言资源创建

• 批准号: 1629923
• 负责人: Christopher Cieri
• 金额: $ 9.98万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1629923&HistoricalAwards=false
• 关键词: CI; Planning; Scalable; Language; Resource

Advances in human language technologies enable systems that, for example, obey natural language commands and respond in kind, translate among many language pairs and summarize multilingual news. However, the technology's potential remains largely untapped because the linguistic resources that fuel development still fall far short of need. This community infrastructure planning (CI-P) initiative begins the process of building infrastructure to continuously develop high quality language resources, by employing techniques proven to work in multiple scientific disciplines. Social media, crowd-sourcing, games with a purpose and citizen science show us that human resources are effectively limitless for some activities. By offering human contributors appropriate opportunities and incentives, this project enhances language resource development well beyond what direct funding alone can produce. By removing constraints on participation, designing activities to appeal to multiple communities the project creates educational opportunities for the public including students and under-represented groups. The increase in scale and diversity of data also benefits those working in language related research, education and technology development. The availability of an ever-growing body of resources for an expanding range of languages will permit developers to supply technologies to a greater proportion of the world.This project is the first step in the creation of infrastructure capable of high volume, continuous collection of language data and judgments through: ubiquity, perseverance, comprehensive annotation, automated training and certification, appropriate incentives, task engineering and variants of crowdsourcing. Building upon Linguistic Data Consortium's WebAnn framework, virtual front end web servers provide multiple interfaces to incentivize and engineer linguistic data contributions from targeted groups: linguists, citizen scientists, game players and students. Collection and annotation activities are analyzed into component tasks according to the skills they require and are assigned as appropriate to different workforces using different workflows. The combination of customized interfaces and novel incentive strategies enables ongoing, scalable data collection and annotation resulting in diverse language resources available to the wider Computer and Information Science and Engineering research and education communities.

人类语言技术的进步使系统能够遵守自然语言命令并以实物做出回应，并在许多语言对中翻译并总结了多语言新闻。但是，该技术的潜力在很大程度上仍未开发，因为燃料发展的语言资源仍然远远远远没有需要。这项社区基础设施计划（CI-P）倡议开始了建立基础设施的过程，通过采用被证明在多个科学学科工作的技术来不断发展高质量的语言资源。社交媒体，众包，有目的的游戏和公民科学表明，人力资源在某些活动中实际上是无限的。通过为人类贡献者提供适当的机会和激励措施，该项目增强了语言资源的发展，远远超出了直接资金的产生。通过消除对参与的限制，设计活动以吸引该项目的多个社区为包括学生和代表性不足的群体在内的公众创造教育机会。数据规模和数据多样性的增加也使从事语言相关研究，教育和技术发展的人受益。 The availability of an ever-growing body of resources for an expanding range of languages will permit developers to supply technologies to a greater proportion of the world.This project is the first step in the creation of infrastructure capable of high volume, continuous collection of language data and judgments through: ubiquity, perseverance, comprehensive annotation, automated training and certification, appropriate incentives, task engineering and variants of crowdsourcing.在语言数据联盟的Webann框架的基础上，虚拟前端网络服务器提供了多个接口，以激励和工程师的语言数据贡献来自目标群体：语言学家，公民科学家，游戏玩家和学生。根据所需的技能将收集和注释活动分析为组件任务，并使用不同的工作流程将其分配给不同的劳动力。定制界面和新颖的激励策略的结合可以使持续的，可扩展的数据收集和注释，从而获得更广泛的计算机以及信息科学和工程研究和教育社区的多种语言资源。