陪伴机器人模仿专业护理人员语音的情感语音合成
Emotional Speech Synthesis for Companion Robot to Imitate Professional Caregiver Speech
AI总结：
本文提出一种由语音情感识别器自动提取情感向量并驱动合成器的情感语音合成方法，使陪伴机器人能模仿专业护理人员语音，主观评估显示其可在清晨和深夜分别让老年人更有活力、更平静。
摘要：
当人们试图影响他人做某事时，会下意识地调整自己的语音，使其包含适当的情感信息。为了让机器人以同样的方式影响人，机器人应当能够在说话时模仿人类的各种情感。为此，我们提出了一种用于模仿人类语音中情感状态的语音合成方法。与以往方法相比，我们方法的优势在于调整合成语音情感所需的人工工作量更少。我们的合成器接收一个情感向量，用以表征合成语音的情感。该向量通过使用语音情感识别器从人类话语中自动获得。我们在一个场景中评估了我们的方法：机器人试图通过使用适当情感状态与老年人交谈，来调节其昼夜节律。对于要模仿的目标语音，我们收集了专业护理人员在一天中不同时间对老年人说话时的话语。随后，我们进行了一项主观评估，让老年参与者聆听由我们的方法生成的语音样本。结果表明，聆听这些样本使参与者在清晨感到更有活力，在深夜感到更平静。这表明机器人或许能够调节参与者的昼夜节律，并且机器人有可能以与人相似的方式施加影响。
英文摘要：
When people try to influence others to do something, they subconsciously adjust their speech to include appropriate emotional information. In order for a robot to influence people in the same way, the robot should be able to imitate the range of human emotions when speaking. To achieve this, we propose a speech synthesis method for imitating the emotional states in human speech. In contrast to previous methods, the advantage of our method is that it requires less manual effort to adjust the emotion of the synthesized speech. Our synthesizer receives an emotion vector to characterize the emotion of synthesized speech. The vector is automatically obtained from human utterances by using a speech emotion recognizer. We evaluated our method in a scenario when a robot tries to regulate an elderly person's circadian rhythm by speaking to the person using appropriate emotional states. For the target speech to imitate, we collected utterances from professional caregivers when they speak to elderly people at different times of the day. Then we conducted a subjective evaluation where the elderly participants listened to the speech samples generated by our method. The results showed that listening to the samples made the participants feel more active in the early morning and calmer in the middle of the night. This suggests that the robot may be able to adjust the participants' circadian rhythm and that the robot can potentially exert influence similarly to a person.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
