Prominence-aware automatic speech recognition for conversational speech

• URL: http://arxiv.org/abs/2509.10116v1
• Date: Fri, 12 Sep 2025 10:18:38 GMT
• Title: Prominence-aware automatic speech recognition for conversational speech
• Authors: Julian Linke, Barbara Schuppler,
• Abstract summary: This paper investigates prominence-aware automatic speech recognition.<n>It combines prominence detection and speech recognition for conversational Austrian German.<n>It shows that transformer-based models can effectively encode prosodic information.
• Score: 5.908471365011944
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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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