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TurnTurk-GPT model predicts Turkish conversation turn-taking

By PulseAugur Editorial · [2 sources] ·

Researchers have developed TurnTurk-GPT, a model fine-tuned from a Turkish GPT-2 to predict turn-taking in conversations. This model demonstrates superior performance compared to multilingual detectors and a zero-shot Turkish language model on specific evaluation metrics. The research highlights that Turkish turn-taking cues are strongly linked to verb-final morphology, with suffix removal on turn-final words significantly impacting prediction accuracy. AI

IMPACT This research could improve the accuracy of speech recognition and dialogue systems for Turkish speakers.

RANK_REASON The cluster describes a research paper detailing a new model for a specific language task.

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

TurnTurk-GPT model predicts Turkish conversation turn-taking

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Ahmet Tu\u{g}rul Bayrak, Fatma Nur Korkmaz, Nur Ya\u{g}mur Tuncer, Mustafa Serta\c{c} T\"urkel ·

    TurnTurk-GPT: Text-Based Turn-Taking Prediction for Turkish

    arXiv:2610.42010v1 Announce Type: new Abstract: This paper presents TurnTurk-GPT, a text-based turn-taking predictor for Turkish obtained by fine-tuning a Turkish GPT-2 model with the TurnGPT objective on synthetic and real dialogue, and evaluates it on real Turkish conversation …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    TurnTurk-GPT: Text-Based Turn-Taking Prediction for Turkish

    TurnTurk-GPT, a Turkish turn-taking predictor fine-tuned from GPT-2, outperforms multilingual detectors and reveals that Turkish end-of-turn cues rely on verb-final morphology.

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