RIDIR: Collaborative Research: Enabling Access to and Analysis of Shared Daylong Child and Family Audio Data

儿童在生命最初几年的语言发展预示着其长期的认知发展、学业成就和成年后的预期收入。反过来，早期的语言发展取决于与成人的语言互动。越来越多的研究人员使用全天的录音来研究儿童语言发展和儿童照顾者的互动。与简短的语言样本相比，全天的录音记录了孩子一天中所有的经历。全天录音也被用于应用设置。例如，研究表明，到一年级时，社会经济背景较高的孩子比社会经济背景较低的孩子多听到数千万个单词，使社会不平等永久化。多个针对低社会经济家庭的大规模干预项目，包括芝加哥的“三百万字倡议”和“普罗维登斯谈话”项目，都在使用全天的录音，向父母提供自动、个性化的反馈，告诉他们的孩子何时、多久听到成人的话，以及经历对话的转变。全天录音的特点，有利于研究人员和从业人员也提出了独特的挑战。首先，它们的长持续时间对于研究儿童-成人互动的时间动态是理想的，但是利用长持续时间需要使用自动语音识别技术。目前的自动语音识别系统在儿童语音识别方面存在困难，并且受到录音中嘈杂和变化的声学环境的挑战。另一个挑战是，这些录音捕捉到的私人时刻需要长时间的人工倾听才能删除。这使得研究人员很难公开分享录音，因此，个别研究实验室收集的录音的潜在价值没有得到充分实现。这个项目将创建一个名为HomeBank的新资源，它将有三个关键组成部分：(1)包含人类听众删除私人信息的全天录音的公共数据集；(2)包含未删除私人信息的录音时间约10至100倍的更大数据集，这些录音时间将是免费的，但仅限于那些受过人类研究伦理培训的人；(3)自动分析全天录音的计算机程序的开源存储库。HomeBank将利用现有的网络基础设施TalkBank来共享语言数据。数据集中包含的全天录音将代表典型的发展和临床群体，从新生儿到学龄儿童的年龄范围，以及语言和社会经济背景的范围。我们希望主要用户是基础和应用儿童发展研究人员以及开发自动语音识别技术的工程师。免费访问的数据库和开源计算机程序将最终改善早期干预所依据的数据，并为父母提供反馈他们为孩子提供语言输入的可用工具。

A child's language development in the first few years of life predicts long-term cognitive development, academic achievement, and expected income as an adult. Early language development in turn depends on linguistic interactions with adults. Increasingly, researchers are using daylong audio recordings to study child language development and child-caregiver interactions. Compared to short language samples, daylong recordings capture the full range of experiences a child has over the course of a day. Daylong audio recordings are also being used in applied settings. For example, studies show that by the time they enter First Grade, children from higher socioeconomic backgrounds hear tens of millions more words than children from lower socioeconomic backgrounds, perpetuating social inequalities. Multiple large-scale intervention projects targeting low socioeconomic households, including the Thirty Million Words Initiative in Chicago and the Providence Talks program, are using daylong audio recordings to provide automated, personalized feedback to parents on when and how often their child hears adult words and experiences conversational turns. The features of daylong recordings that are advantageous for researchers and practitioners also pose unique challenges. For one, their long durations are ideal for studying the temporal dynamics of child-adult interaction, but taking advantage of the long durations requires the enlistment of automated speech recognition technology. Current automatic speech recognition systems have difficulties with child speech and are challenged by the noisy and varied acoustic environments represented in the recordings. Another challenge is that the recordings capture private moments that require long hours of human listening to remove. This makes it difficult for researchers to share the recordings publicly, so that the potential value of the recordings collected by individual research labs is not fully realized.This project will create a new resource, called HomeBank, that will have three key components: (1) a public dataset containing daylong audio recordings that have had private information removed by human listeners, (2) a larger dataset containing about ten to one hundred times as many hours of recording that have not had private information removed and will be free but restricted to those who have demonstrated training in human research ethics, and (3) an open-source repository of computer programs to automatically analyze the daylong audio recordings. HomeBank will take advantage of an existing cyberinfrastructure for sharing linguistic data called TalkBank. The daylong audio recordings included in the datasets will represent both typically developing and clinical groups, a range of ages from newborn infants to school age children, and a range of language and socioeconomic backgrounds. We expect the primary users to be basic and applied child development researchers as well as engineers developing automatic speech recognition technologies. The free-to-access database and the open source computer programs will ultimately improve both the data on which early interventions are based and the tools available for providing parents with feedback on the linguistic input they provide their children.