Seoyoung Kim

Is the Same Performance Really the Same?: Understanding How Listeners Perceive ASR Results Differently According to the Speaker's Accent

2024 · Proceedings of the ACM on Human-Computer Interaction

Research suggests that automatic speech recognition (ASR) systems, which automatically convert speech to text, show different performances according to various input classes (e.g., accent, age), requiring attention to building fairer AI systems that would perform …

Beyond Prompts: Learning from Human Communication for Enhanced AI Intent Alignment

2024 · arXiv (Cornell University)

AI intent alignment, ensuring that AI produces outcomes as intended by users, is a critical challenge in human-AI interaction. The emergence of generative AI, including LLMs, has intensified the significance of this problem, as interactions …

RAISE: leveraging responsible AI for service excellence

2024 · Journal of service management

Purpose This article introduces the Responsible AI for Service Excellence (RAISE) framework. RAISE is a strategic framework for responsibly integrating AI into service industries. It emphasizes collaborative AI design and deployment that aligns with the …