Comparing alignment toward American, British, and Indian English text-to-speech (TTS) voices: influence of social attitudes and talker guise - Dodd, Nicole; Cohn, Michelle; Zellou, Georgia (Frontiers in Computer Science, 2023)
Text-to-speech (TTS) voices, which vary in their apparent native language and dialect, are increasingly widespread. In this paper, we test how speakers perceive and align toward TTS voices that represent American, British, and Indian dialects of English and the extent that social attitudes shape patterns of convergence and divergence. We also test whether top-down knowledge of the talker, manipulated as a “human” or “device” guise, mediates these attitudes and accommodation. Forty-six American English-speaking participants completed identical interactions with 6 talkers (2 from each dialect) and rated each talker on a variety of social factors. Accommodation was assessed with AXB perceptual similarity by a separate group of raters. Results show that speakers had the strongest positive social attitudes toward the Indian English voices and converged toward them more. Conversely, speakers rate the American English voices as less human-like and diverge from them. Finally, speakers overall show more accommodation toward TTS voices that were presented in a “human” guise. We discuss these results through the lens of the Communication Accommodation Theory (CAT).