NaturalTurn: A Method to Segment Speech into Psychologically Meaningful Conversational Turns
This provides a scalable method for researchers in conversation science to analyze turn-taking dynamics in large datasets, linking them to social outcomes, but it is incremental as it builds on existing transcript-processing methods.
The paper tackles the problem of segmenting speech-to-text transcripts into conversational turns, introducing NaturalTurn, an algorithm that distinguishes primary turns from secondary utterances like backchannels, and shows it captures turns more accurately than a baseline, with improvements in matching empirical durations and revealing linguistic alignment patterns.
Conversation is a subject of increasing interest in the social, cognitive, and computational sciences. Yet as conversational datasets continue to increase in size and complexity, researchers lack scalable methods to segment speech-to-text transcripts into conversational "turns"-the basic building blocks of social interaction. We discuss this challenge and then introduce "NaturalTurn," a turn-segmentation algorithm designed to accurately capture the dynamics of conversational exchange. NaturalTurn operates by distinguishing speakers' primary conversational turns from listeners' secondary utterances, such as backchannels, brief interjections, and other forms of parallel speech that characterize human conversation. Using data from a large conversation corpus, we show that NaturalTurn captures conversational turns more accurately than a baseline model. For example, it produces turns with durations and gaps that match empirical literature, reveals stronger linguistic alignment patterns between speakers, and uncovers otherwise hidden relationships between turn-taking and affective outcomes. NaturalTurn thus represents a pragmatic development in machine-generated transcript-processing methods, or "turn models", that will enable researchers to link turn-taking dynamics with important outcomes of social interaction, a central goal of conversation science.