Quantifying the perceptual value of lexical and non-lexical channels in speech

Abstract

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.

Publication
published in Interspeech 2023; Dublin, Ireland

In Interspeech 2023; Dublin, Ireland

Sarenne Wallbridge
Sarenne Wallbridge
Machine Learning PhD Student

My research interests include machine learning, pyscholinguistics, and information theory.

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