Cross-Layer Models for Low-Resource Conversational ASR

Attend this plenary lecture from JSALT 2025 exploring cross-layer models for automatic speech recognition in conversational settings. Learn how Barbara Schuppler from TU Graz applies cross-layer optimization principles from communications engineering to access meaning across multiple levels of speech information. Discover findings on integrating pronunciation and prosodic variation into ASR systems for conversational speech through hybrid approaches that combine data-driven and knowledge-based methods. Examine how these techniques prove particularly effective in low-resource settings and understand why classical systems paired with linguistic knowledge can still outperform transformer-based models for short, fragmented utterances. Explore applications beyond ASR including pathological speech analysis, dementia prediction, and assistive speech technologies. Gain insights into quantitative analyses of prosody and pronunciation variation in conversational speech, and understand how phonetic and linguistic knowledge can be integrated into speech technology for educational and healthcare applications.