Linganisha mbinu

	Uainishaji wa Kitendo cha Mazungumzo	Utendaji wa Utambuzi wa Nia
Nyanja	Uchimbaji wa Matini	Uchimbaji wa Matini
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1997–2000	—
Mwanzilishi	Stolcke et al.; Jurafsky et al.	—
Aina	NLP utterance-classification task	NLP / NLU text-classification task
Chanzo asilia	Stolcke, A. et al. (2000). Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech. Computational Linguistics, 26(3), 339-373.	Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP.
Majina mbadala	dialogue act tagging, speech act classification, Diyalog Eylem Sınıflandırma (Dialogue Act Classification)	intent classification, intent recognition, Niyet Tespiti (Intent Detection)
Zinazohusiana	4	4
Muhtasari	Dialogue act classification is a natural-language-processing task that automatically labels the communicative function of each utterance in a conversation — such as question, answer, greeting, or rejection. Consolidated by Jurafsky et al. (1997) and Stolcke et al. (2000), it is a foundational component for chatbots and discourse analysis.	Intent detection is a natural-language-understanding task that classifies the purpose behind a user utterance — such as making a reservation, asking for information, or filing a complaint — into one of a set of predefined intent classes. It is a core NLU component of conversational interfaces and customer-service automation systems, drawing on the benchmarks of Larson et al. (2019) and Casanueva et al. (2020).