Computer-based auditory skill building program for aural (re)habilitation

描述（由申请人提供）：根据MarkeTrak VII调查（Kochkin 2008），美国大约有3500万人有不同程度的听力损失。其中，近1000万人有助听器，67000人有人工耳蜗。听觉（再）康复（AR）项目的目标是建立听力损失个体的听力技能，使他们能够在他们的环境中理解语言。有了适当的助听器和增强现实，听力损失的人可以开始辨别和识别周围口语中的语音。在这个项目的第一阶段，我们开发了一个自适应计算机引导的AR软件程序，称为声音识别导师（SIT），专注于声音识别和辨别。有关SIT的视频演示，请访问http://www.biospeech.com/research/ar.html。SIT提供一个自动序列的声音目标进行训练，并根据用户的表现选择目标的类型。它还选择以听觉或视听方式呈现目标。SIT使用所有单词目标的自然人类视听记录。它还使用儿童友好的简单文字图像，使这个软件适合和有趣的孩子。对24名儿童和成人进行的软件评估结果表明，在10个疗程的过程中，受试者的声音识别技能显著提高。与成人相比，儿童从自动化课程中获益更多。成年人倾向于选择自己的声音目标进行训练。此外，我们发现受试者在经过训练的特定声音目标上有所提高，但未经过训练的前测中有问题的目标在后测中没有提高。这表明了这样一个事实，即改善不是由增加语音暴露引起的，而是通过训练特定的声音目标引起的。在这个第二阶段的提案中，我们将扩展SIT并将其开发成可销售的产品。该建议包括以下目标：(i)编制技术支助方案的西班牙文版本；（ii）在可选的背景噪音和多个说话者的情况下，将单词嵌入句子中来扩展SIT；（iii）扩大科技辅助小组的开放式训练模式；（iv）扩展SIT以创建DVD安装程序，与Web接口，并开发家庭登录UI；(v)评估专门供家庭使用的方案；（vi）制订内建的评估方案，以制订针对使用者的聆听干预计划

DESCRIPTION (provided by applicant): According to the MarkeTrak VII survey (Kochkin 2008), there are roughly 35 million individuals in the US with some degree of hearing loss. Of these, almost 10 million have hearing aids and 67,000 have cochlear implants. The goal of auditory (re)habilitation (AR) programs is to build the listening skills of individuals with hearing loss, so that they can comprehend the language in their environment. With appropriate hearing devices and AR, individuals with hearing loss can begin to discriminate and identify the speech sounds in the spoken language around them. In Phase I of this project we developed an adaptive computer-guided AR software program called the Sound Identification Tutor (SIT) that focused on sound identification and discrimination. For a video demonstration showcasing the SIT please visit http://www.biospeech.com/research/ar.html. The SIT provides an automated sequence of sound targets to be trained and it chooses the type of target depending on the performance of the user. It also chooses whether to present the target in auditory or audiovisual mode. The SIT uses natural human audiovisual recordings of all the word targets. It also uses child-friendly images of simple words to make this software suitable and fun for children. The results of an evaluation of the software with 24 children and adults showed that over a course of 10 sessions subjects significantly improved their sound identification skills. Children benefitted more from the automated lesson sequence than adults. Adults tended to prefer to choose their own sound targets to train on. In addition, we showed that subjects improved on specific sound targets they trained on, but problematic targets from the pre-test that were not trained on did not improve in the post-test. This showcases the fact that improvements were not caused by increased exposure to speech but by training specific sound targets. In this Phase II proposal, we will extend the SIT and develop it into a marketable product. The proposal consists of the following aims: (i) To Build a Spanish Version of the SIT; (ii) To Extend the SIT with Words Embedded in Sentences with Optional Background Noise and Multiple Speakers; (iii) To Extend the Open- Ended Training Module of the SIT; (iv) To Expand the SIT to Create a DVD installer, Interface with the Web, and Develop an In-home Login UI; (v) To Evaluate the Program Specifically for In-home Use; (vi) To Create a Built-in Assessment Protocol to Produce User-specific Listening Intervention Plans PUBLIC HEALTH RELEVANCE: In the United States, there are roughly 35 million individuals with some degree of hearing loss and of these, almost 10 million have hearing aids and 67,000 have cochlear implants who need intensive auditory (re)habilitation (AR) training to fully realize the potential benefit of their prostheses and attain intelligible speech. Face-to-face AR training with a specialist is expensive, not always covered by insurance and not always feasible because clients may not have access to a specialist, esp. if they speak a different language. The proposed project will expand upon an adaptive computer-guided software program (the Speech Identification Tutor, SIT) that focuses on learning phoneme discrimination and identification and will provide a Spanish version of the software, provide additional synthetic voices for open-ended training, provide an additional adaptive sentence task where individuals are exposed to words embedded in sentences, with background noise, and multiple speakers and will be evaluated for in-home use by a larger group of users.