This paper presents a study on mutual speech variation influences in a human-computer setting. The study highlights behavioral patterns in data collected as part of a shadowing experiment, and is performed using a novel end-to-end platform for studying phonetic variation in dialogue. It includes a spoken dialogue system capable of detecting and tracking the state of phonetic features in the user’s speech and adapting accordingly. It provides visual and numeric representations of the changes in real time, offering a high degree of customization, and can be used for simulating or reproducing speech variation scenarios. The replicated experiment presented in this paper along with the analysis of the relationship between the human and non-human interlocutors lays the groundwork for a spoken dialogue system with personalized speaking style, which we expect will improve the naturalness and efficiency of human-computer interaction.
Integrating support for changes in the speech signal into computer systems may enhance hci and provide improved tools for studying convergence in hci . @cite_25 discusses the advantages of systems that dynamically adapt their speech output to that of the user, and the challenges involved in developing and using these systems.
@cite_25
2042159198
The design of robust interfaces that process conversational speech is a challenging research direction largely because users' spoken language is so variable. This research explored a new dimension of speaker stylistic variation by examining whether users' speech converges systematically with the text-to-speech (TTS) heard from a software partner. To pursue this question, a study was conducted in which twenty-four 7 to 10-year-old children conversed with animated partners that embodied different TTS voices. An analysis of children's amplitude, durational features, and dialogue response latencies confirmed that they spontaneously adapt several basic acoustic-prosodic features of their speech 10--50p, with the largest adaptations involving utterance pause structure and amplitude. Children's speech adaptations were relatively rapid, bidirectional, and dynamically readaptable when introduced to new partners, and generalized across different types of users and TTS voices. Adaptations also occurred consistently, with 70--95p of children converging with their partner's TTS, although individual differences in magnitude of adaptation were evident. In the design of future conversational systems, users' spontaneous convergence could be exploited to guide their speech within system processing bounds, thereby enhancing robustness. Adaptive system processing could yield further significant performance gains. The long-term goal of this research is the development of predictive models of human-computer communication to guide the design of new conversational interfaces.