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Social Perceptions of Synthetic Speakers

A rapidly growing interest in human-computer interactions and spoken dialog systems has been observed in the last couple of years. Chatbots are becoming increasingly predominant, especially for customer service and personal companions and assistants. Main efforts are being undertaken on automatic speech recognition (ASR) and natural language understanding (NLU), facing challenges such as background noise in rooms, overlapping speech, and understanding context. Besides recognizing spoken sentences and interpreting users’ intentions, the dialog strategy should pursue a satisfactory natural and assistive communication with users. With the need of providing personalized, tailored solutions based on users' individual behavior and preferences, adaptive voice-based interactions are today’s focus of numerous applications in academia and in industry.


In view of the work motivation, the following research questions can be defined:

1. Identification of user’s positive and negative attributions of synthetic voices. What speaker social attributions elicit synthetic voices? How can these attributions be assessed?

2. Definition of acoustic correlates of attributions of synthetic voices.

3. Transformation of voice attributions into negative and positive ones.

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