Quantifying the perceptual value of lexical and non-lexical channels in speech
Wallbridge, Sarenne, Bell, Peter, Lai, Catherine
–arXiv.org Artificial Intelligence
Speech is a fundamental means of communication that can be seen to provide two channels for transmitting information: the lexical channel of which words are said, and the non-lexical channel of how they are spoken. Both channels shape listener expectations of upcoming communication; however, directly quantifying their relative effect on expectations is challenging. Previous attempts require spoken variations of lexically-equivalent dialogue turns or conspicuous acoustic manipulations. This paper introduces a generalised paradigm to study the value of non-lexical information in dialogue across unconstrained lexical content. By quantifying the perceptual value of the non-lexical channel with both accuracy and entropy reduction, we show that non-lexical information produces a consistent effect on expectations of upcoming dialogue: even when it leads to poorer discriminative turn judgements than lexical content alone, it yields higher consensus among participants.
arXiv.org Artificial Intelligence
Jul-7-2023
- Country:
- North America > United States (0.14)
- Genre:
- Research Report
- Experimental Study (0.47)
- New Finding (0.46)
- Research Report
- Technology: