Papers by Malolan Chetlur
Scaling Neural ITN for Numbers and Temporal Expressions in Tamil: Findings for an Agglutinative Low-resource Language (2023.emnlp-industry)
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| Challenge: | Inverse Text Normalisation (ITN) is a textrewriting task that converts verbalized text to written form. |
| Approach: | They propose to use a seq2seq model, a non-autoregressive text editor and a sequence tagger + rules combination to fine-tune three pre-trained neural models. |
| Outcome: | The proposed model improves with bootstrapping and data augmentation, and bootstrap alone shows a percentage improvement of 14.12 %. |
Unifying Streaming and Non-streaming Zipformer-based ASR (2025.acl-industry)
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Bidisha Sharma, Karthik Pandia D S, Shankar Venkatesan, Jeena J Prakash, Shashi Kumar, Malolan Chetlur, Andreas Stolcke
| Challenge: | Existing frameworks for streaming and non-streaming ASR models have been used to reduce development, training and deployment costs. |
| Approach: | They propose to use dynamic right-context through chunked attention masking to train zipformer-based ASR models. |
| Outcome: | The proposed framework reduces word error by relative 7.9% with a small degradation in user-perceived latency. |