Papers by Christoph Schmidt
Data-Driven Pronunciation Modeling of Swiss German Dialectal Speech for Automatic Speech Recognition (L18-1)
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| Challenge: | a Swiss German speech recognizer is trained using a standard German annotation model. |
| Approach: | They propose to train a Swiss German speech recognition system using a standard German annotation model. |
| Outcome: | The proposed system is based on a standard German annotation model and a grapheme-to-phoneme conversion model. |
GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark (2026.findings-acl)
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| Challenge: | Authorship verification (AV) is a task of determining whether two texts were written by the same author. |
| Approach: | They propose a benchmark for German AV comprising over 400k labeled text pairs. |
| Outcome: | The proposed model outperforms baselines and state-of-the-art models by 0.09 and surpasses GPT-5 in a zero-shot setting by 0.08. |
Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications - A Case Study on German Oral History Interviews (2020.lrec-1)
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| Challenge: | Current automatic speech recognition systems show remarkable performance when adequate data is used for training. |
| Approach: | They propose to perform a robust acoustic model adaption to a target domain in a cross-lingual manner. |
| Outcome: | The proposed approach reduces word error rate by more than 30% on German oral history interviews compared to a model trained from scratch on the target domain and 6-7% on same-language out-of-domain training data. |