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Register a new userLarge-scale text pre-training helps with dialogue act recognition, but not without fine-tuning
تساعد النص المسبق على نطاق واسع في التعرف على قانون الحوار، ولكن ليس بدون ضبط جيد
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نحن نستخدم التعرف على قانون الحوار (دار) للتحقيق في مدى امتثال بيرت الانتحال في الحوار، وكيف تساهم بضبط الدقيقة والتدريب المسبق على نطاق واسع في أدائها.نجد أنه في حين أن كل من التدريبات القياسية السابقة للتدريب والإحاطاء على البيانات التي تشبه الحوار هي مفيدة، فإن الضبط الدقيق الخاص بمهارات المهام أمر ضروري للأداء الجيد.
We use dialogue act recognition (DAR) to investigate how well BERT represents utterances in dialogue, and how fine-tuning and large-scale pre-training contribute to its performance. We find that while both the standard BERT pre-training and pretraining on dialogue-like data are useful, task-specific fine-tuning is essential for good performance.
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This study proposes an utterance position-aware approach for a neural network-based dialogue act recognition (DAR) model, which incorporates positional encoding for utterance's absolute or relative position. The proposed approach is inspired by the o
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