This paper reports the improvements we made to our previously proposed hidden Markov model (HMM) based summarization method for multi-domain contact center�...
ABSTRACT. This paper reports the improvements we made to our previ- ously proposed hidden Markov model (HMM) based summa- rization method for multi-domain�...
Improvements: New ILP formulation. •Objective: Extractive summarization of multi-domain contact center dialogues. (Domains: finance, PC support, ISP,�...
Improving hmm-based extractive summarization for multi-domain contact center dialogues ; Analysis of listening-oriented dialogue for building listening agents.
A method to improve the quality of extractive summarization for contact center dialogues in various domains by making use of training samples whose domains�...
A novel extractive summarization method for contact center dialogues using a particular type of hidden Markov model (HMM) called Class Speaker HMM (CSHMM),�...
This method enhances summarization efficiency by giving prominence to key sentences and minimizing peripheral information. Additionally, we conducted ablation�...
Missing: hmm- dialogues.
PDF | This paper proposes a novel extractive summarization method for speech dialo- gues between agents and customers in contact centers. The proposed.
Mar 5, 2024 � This study of dialog summarization covers multi-domain, multimodal and multilingual datasets, and the potential challenges in the different�...
Learning to model domain-specific utterance sequences for extractive summarization of contact center dialogues. R Higashinaka, Y Minami, H Nishikawa, K Dohsaka,�...