Papers by Mathew Magimai Doss
An HMM Approach with Inherent Model Selection for Sign Language and Gesture Recognition (2020.lrec-1)
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| Challenge: | despite the extensive use of HMMs for sign recognition, determining the HMM structure remains a challenge . despite their success in modeling sequential and multivariate data, establishing the structure remains challenging . |
| Approach: | They propose a continuous HMM framework for modeling and recognizing isolated signs . they propose to optimize the number of states for each sign separately during recognition . |
| Outcome: | The proposed model performs better on three different datasets and is competitive with existing models. |
kNN Retrieval for Simple and Effective Zero-Shot Multi-speaker Text-to-Speech (2025.naacl-short)
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| Challenge: | Neural text-to-speech (TTS) models typically rely on extensive transcribed speech datasets and intricate training pipelines. |
| Approach: | They propose a framework for zero-shot multi-speaker text-to-speech using retrieval methods which leverage the linear relationships between SSL features. |
| Outcome: | The proposed framework achieves comparable performance to state-of-the-art models trained on large training datasets. |