Papers by Sean Leishman
Analysing the role of lexical and temporal information in turn-taking through predictability (2026.eacl-long)
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| Challenge: | Existing evaluations of spoken dialogue systems do not address which information sources drive predictions. |
| Approach: | They examine the role of lexical-temporal features on the predictability of turn structure by examining PairwiseTurnGPT, a full-duplex model of spoken dialogue transcripts. |
| Outcome: | The proposed model can produce fluent conversational output, but it does not guarantee realistic turn-taking behaviour. |