We present a Wizard-of-Oz experiment examining phonetic accommodation of human interlocutors in the context of human-computer interaction. Forty-two native speakers of German engaged in dynamic spoken interaction with a simulated virtual tutor for learning the German language called . Mirabella was controlled by the experimenter and used either natural or hidden Markov model-based synthetic speech to communicate with the participants. In the course of four tasks, the participants’ accommodating behavior with respect to wh-question realization and allophonic variation in German was tested. The participants converged to Mirabella with respect to modified wh-question intonation, i.e., rising F contour and nuclear pitch accent on the interrogative pronoun, and the allophonic contrast [ɪç] vs.[ɪk] occurring in the word ending -ig. They did not accommodate to the allophonic contrast [ɛː] vs.[eː] as a realization of the long vowel -ä-. The results did not differ between the experimental groups that communicated with either the natural or the synthetic speech version of Mirabella. Testing the influence of the “Big Five” personality traits on the accommodating behavior revealed a tendency for neuroticism to influence the convergence of question intonation. On the level of individual speakers, we found considerable variation with respect to the degree and direction of accommodation. We conclude that phonetic accommodation on the level of local prosody and segmental pronunciation occurs in users of spoken dialog systems, which could be exploited in the context of computer-assisted language learning.

中文翻译：

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与虚拟语言学习导师互动中的语音调节：绿野仙踪研究

我们提出了一个绿野仙踪实验，检查人机交互背景下人类对话者的语音适应。四十二位德语母语人士与模拟虚拟导师进行动态口语互动，学习德语。米拉贝拉由实验者控制，并使用自然或隐藏的基于马尔可夫模型的合成语音与参与者进行交流。在四项任务的过程中，测试了参与者对 wh 问题实现和德语异音变化的适应行为。参与者在修改后的 wh 疑问句语调方面趋于米拉贝拉 (Mirabella)，即疑问代词上的上升 F 轮廓和核音高重音，以及词尾 -ig 中出现的异音对比 [ɪç] 与 [ɪk]。他们没有适应异音对比 [ɛː] 与 [eː] 作为长元音 -ä- 的实现。使用自然或合成语音版本的米拉贝拉进行交流的实验组之间的结果没有差异。测试“大五”人格特征对迁就行为的影响揭示了神经质倾向影响问题语调的收敛。在个体说话者的水平上，我们发现在适应的程度和方向方面存在相当大的差异。我们得出的结论是，口语对话系统的用户会在本地韵律和分段发音水平上进行语音适应，这可以在计算机辅助语言学习的背景下加以利用。