lightbulbPractical problemDialogue System Management and Error Handling
In multitask dialogue, listeners missing content can cause misunderstandings or communication breakdowns.LLM and Natural Language Interaction / Dialogue System Management and Error Handling
In multitask dialogue, listeners missing content can cause misunderstandings or communication breakdowns.
Similar questions
lightbulbPractical problemDialogue System Management and Error Handling
Older adults struggle to find suitable opportunities and partners for reminiscence conversations.lightbulbPractical problemDialogue System Management and Error Handling
Voice ordering systems in the restaurant industry often cause poor customer experience due to recognition errors.lightbulbPractical problemDialogue System Management and Error Handling
Lay users cannot efficiently extract and utilize information from online tabular data.CUI '24Automatic Generation of Conversational Interfaces for Tabular Data Analysis
lightbulbPractical problemDialogue System Management and Error Handling
Users feel frustrated when AI refuses requests and struggle to understand the reasons for refusal.lightbulbPractical problemDialogue System Management and Error Handling
Existing conversational systems cannot naturally switch between chat and task-processing modes, degrading user experience.lightbulbPractical problemDialogue System Management and Error Handling
Current conversational systems are unnatural in multi-party dialogue, easily frustrating users.CUI '23You Don’t Need to Speak, You Need to Listen: Robot Interaction and Human-Like Turn-Taking
Related papers
CHI 2025
Chorus of the Past: Toward Designing a Multi-agent Conversational Reminiscence System with Digital Artifacts for Older Adults
Jingwei Sun, Zhongyue Zhang, Mengyang Wang
CHI 2025
Diagnosing and Prioritizing Issues in Automated Order-Taking Systems: A Machine-Assisted Error Discovery Approach
Maeda F Hanafi, Frederick Reiss, Yannis Katsis
IUI 2024
SCAINs Presenter: Preventing Miscommunication by Detecting Context-Dependent Utterances in Spoken Dialogue
Aoto Tsuchiya, Tomoyuki Maekawa, Michita Imai
CHI 2024
“As an AI language model, I cannot”: Investigating LLM Denials of User Requests
Joel Wester, Tim Schrills, Henning Pohl
CUI 2023
Unified Conversational Models with System-Initiated Transitions between Chit-Chat and Task-Oriented Dialogues
Ye Liu, Stefan Ultes, Wolfgang Minker