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Individualized feedback in computer-assisted spoken language learning

计算机辅助口语学习中的个性化反馈

基本信息

批准号：
230875573
负责人：
Professor Dr. Bernd Möbius
金额：
--
依托单位：
LORIA - Laboratoire lorrain de recherche en informatique et ses applications (UMR 7503)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2013
资助国家：
德国
起止时间：
2012-12-31 至 2015-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/230875573?language=en
关键词：
Individualized feedback computer assisted spoken

项目摘要

The overall aim of the project is to gain an order of magnitude in the usability and efficiency of computer-assisted language learning software by adapting content, feedback and exercises to individual learners in the speech dimension of a foreign language. This will be achieved by integrating the production and perception of the learner's own speech and focusing on the French-German language pair, in both directions.Difficulties experienced by learners depend on the phonology of their native language and are thus non-symmetric. A particular strength of the project is to involve speech scientists who have worked extensively on the phonetics and phonology of the two languages, and especially in cross-linguistic contexts.Providing learners with feedback is a central issue of foreign language learning. The first objective is to provide the learner with automated feedback which derives from an analysis of the learner's utterance and targets specifically the acoustic features to be improved. The second objective is to offer feedback that relies on phonetic knowledge incorporated in the learning system and interacts relevantly with automatic speech recognition (ASR) and signal processing. This means that confidence in the results returned by ASR will be taken into account to derive diagnoses and feedback: the higher the confidence the more explicit the level of feedback.The third objective is to reach a high level of individualization of the user interface, type of exercises, nature and level of feedback (textual, acoustic, visual) and to develop a learner profile, taking into account the phonetic difficulties experienced by the individual learner on the levels of production and perception. A key aspect consists of using the learner's own voice.During a training session, the learner will be exposed to modified versions of his/her own production. This will enable the learner to measure the learning progress by a comparison of his/her own realizations with the feedback proposed by the system. This objective requires a precise definition of the phonetic difficulties predicted for the L1-L2 pair by speech scientists of both languages. These difficulties concern the segmental level (e.g., stop aspiration, final devoicing, vowel quantity) and the suprasegmental level (e.g., lexical stress, contrastive accent). The target features will be selected by considering the phonological and phonetic systems of both languages and ranked by observed recurring errors made by learners, to ensure a relevant learning progress. This procedure will be driven by a careful analysis of a corpus comprising French and German L2 speech data recorded by learners at different levels of proficiency. This corpus will be made available to the scientific community.The project will rely on a tight interaction between phonetics/speech science and signal processing/speech recognition, which is both necessary and expected to be efficient for the project proposed here.

该项目的总体目标是通过在外语语音维度上针对个体学习者调整内容、反馈和练习，使计算机辅助语言学习软件的可用性和效率提高一个数量级。这将通过整合学习者自己语音的产生和感知并在两个方向上关注法语-德语对来实现。学习者遇到的困难取决于其母语的音系，因此是非对称的。该项目的一个特殊优势是让语音科学家参与其中，他们在两种语言的语音学和音系学方面进行了广泛的研究，特别是在跨语言环境中。为学习者提供反馈是外语学习的核心问题。第一个目标是为学习者提供自动反馈，该反馈来自对学习者话语的分析，并专门针对要改进的声学特征。第二个目标是提供依赖于学习系统中纳入的语音知识的反馈，并与自动语音识别 (ASR) 和信号处理相关地交互。这意味着在得出诊断和反馈时将考虑对 ASR 返回结果的置信度：置信度越高，反馈水平越明确。第三个目标是达到用户界面、练习类型、反馈性质和水平（文本、听觉、视觉）的高水平个性化，并开发学习者档案，同时考虑到个体学习者在生产和感知水平上遇到的语音困难。一个关键方面包括使用学习者自己的声音。在培训课程中，学习者将接触到他/她自己作品的修改版本。这将使学习者能够通过将他/她自己的认识与系统提出的反馈进行比较来衡量学习进度。这一目标需要两种语言的语音科学家对 L1-L2 对预测的语音困难进行精确定义。这些困难涉及音段水平（例如，停送气、末清音、元音数量）和超音段水平（例如，词汇重音、对比重音）。将考虑两种语言的语音和语音系统来选择目标特征，并根据观察到的学习者重复出现的错误进行排名，以确保相关的学习进度。这一过程将通过对由不同熟练程度的学习者记录的法语和德语 L2 语音数据的语料库进行仔细分析来驱动。该语料库将提供给科学界。该项目将依赖于语音学/语音科学和信号处理/语音识别之间的紧密互动，这对于此处提出的项目来说既是必要的，也是有效的。