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arXiv · 2509.10116

Prominence-aware automatic speech recognition for conversational speech

Julian Linke·Barbara Schuppler
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Abstract

This paper investigates prominence-aware automatic speech recognition (ASR) by combining prominence detection and speech recognition for conversational Austrian German. First, prominence detectors were developed by fine-tuning wav2vec2 models to classify word-level prominence. The detector was then used to automatically annotate prosodic prominence in a large corpus. Based on those annotations, we trained novel prominence-aware ASR systems that simultaneously transcribe words and their prominence levels. The integration of prominence information did not change performance compared to our baseline ASR system, while reaching a prominence detection accuracy of 85.53% for utterances where the recognized word sequence was correct. This paper shows that transformer-based models can effectively encode prosodic information and represents a novel contribution to prosody-enhanced ASR, with potential applications for linguistic research and prosody-informed dialogue systems.

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BibTeXRIS

Julian Linke, Barbara Schuppler. 2025-09-12. Prominence-aware automatic speech recognition for conversational speech. https://arxiv.org/abs/2509.10116

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