6 papers · 2 filters
KIT's Low-resource Speech Translation Systems for IWSLT2025: System Enhancement with Synthetic Data and Model Regularization
Zhaolin Li, Yining Liu, Danni Liu +6
This paper presents KIT's submissions to the IWSLT 2025 low-resource track. We develop both cascaded systems, consisting of Automatic Speech Recognition (ASR) and Machine Translati…
Adapting Language Balance in Code-Switching Speech
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Despite achieving impressive results on standard benchmarks, large foundational models still struggle against code-switching test cases. When data scarcity cannot be used as the us…
Bayesian Low-Rank Factorization for Robust Model Adaptation
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Large speech foundation models achieve strong performance across many domains, but they often require adaptation to handle local needs such as code-switching, where speakers mix la…
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation
Christian Huber, Tu Anh Dinh, Carlos Mullov +10
The challenge of low-latency speech translation has recently draw significant interest in the research community as shown by several publications and shared tasks. Therefore, it is…
Weight Factorization and Centralization for Continual Learning in Speech Recognition
Enes Yavuz Ugan, Ngoc-Quan Pham, Alexander Waibel
Modern neural network based speech recognition models are required to continually absorb new data without re-training the whole system, especially in downstream applications using…
PIER: A Novel Metric for Evaluating What Matters in Code-Switching
Enes Yavuz Ugan, Ngoc-Quan Pham, Leonard Bärmann +1
Code-switching, the alternation of languages within a single discourse, presents a significant challenge for Automatic Speech Recognition. Despite the unique nature of the task, pe…