Enhancing ASR Performance in the Medical Domain for Dravidian Languages
Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical domains due to limited annotated data and morphological complexity. This work proposes a novel confidence-aware training framework that integrates real and synthetic speech data through a hybrid confidence mechanism combining static perceptual and acoustic similarity metrics with dynamic model entropy. Unlike direct fine-tuning approaches, the proposed methodology employs both fixed-weight and learnable-weight confidence aggregation strategies to guide sample weighting during training, enabling effective utilization of heterogeneous data sourc...
| Authors | Sri Charan Devarakonda, Ravi Sastry Kolluru, Manjula Sri Rayudu et al. |
|---|---|
| Primary category | eess.AS |
| Published | 10 April 2026 |
| Last updated at source | 10 April 2026 |
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