Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914074387808256 |
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| author | Ahadzi, Edem Singh, Vishwanath Pratap Kinnunen, Tomi Hautamaki, Ville |
| author_facet | Ahadzi, Edem Singh, Vishwanath Pratap Kinnunen, Tomi Hautamaki, Ville |
| contents | In this work, we present the first study addressing automatic speech recognition (ASR) for children in an online learning setting. This is particularly important for both child-centric applications and the privacy protection of minors, where training models with sequentially arriving data is critical. The conventional approach of model fine-tuning often suffers from catastrophic forgetting. To tackle this issue, we explore two established techniques: elastic weight consolidation (EWC) and synaptic intelligence (SI). Using a custom protocol on the MyST corpus, tailored to the online learning setting, we achieve relative word error rate (WER) reductions of 5.21% with EWC and 4.36% with SI, compared to the fine-tuning baseline. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_20216 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence Ahadzi, Edem Singh, Vishwanath Pratap Kinnunen, Tomi Hautamaki, Ville Audio and Speech Processing In this work, we present the first study addressing automatic speech recognition (ASR) for children in an online learning setting. This is particularly important for both child-centric applications and the privacy protection of minors, where training models with sequentially arriving data is critical. The conventional approach of model fine-tuning often suffers from catastrophic forgetting. To tackle this issue, we explore two established techniques: elastic weight consolidation (EWC) and synaptic intelligence (SI). Using a custom protocol on the MyST corpus, tailored to the online learning setting, we achieve relative word error rate (WER) reductions of 5.21% with EWC and 4.36% with SI, compared to the fine-tuning baseline. |
| title | Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2505.20216 |