Industry case studies of adapting TTS for smooth interactions

Abstract

Modern, neural-based ASR and TTS systems for speech communication are now very sophisticated, but they are frequently designed for average users in more idealized scenarios, which can underperform when interacting with users having specialized listening needs, or who speak in non-standard ways. Here we review recent TTS research, and note that industrial, production-level implementations of adaptive TTS systems are scarce. We describe how we implemented changes to TTS systems based on prior research, and then report qualitative results from two case studies, where adapted TTS techniques are applied to real-world HRI settings: First, in an older adult care home, and second, in an airport, where noise levels create comprehension problems. Results suggest promising directions using relatively simple modifications to pitch, duration, and intensity of the robot's speech, and offer a framework for larger, more formal studies of how TTS adaptations can improve HRI.

arXiv commentPublished at RO-MAN 2026