Summary of Meralion-speechencoder: Towards a Speech Foundation Model For Singapore and Beyond, by Muhammad Huzaifah et al.
MERaLiON-SpeechEncoder: Towards a Speech Foundation Model for Singapore and Beyond
by Muhammad Huzaifah, Geyu Lin, Tianchi Liu, Hardik B. Sailor, Kye Min Tan, Tarun K. Vangani, Qiongqiong Wang, Jeremy H. M. Wong, Nancy F. Chen, Ai Ti Aw
First submitted to arxiv on: 16 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This technical report introduces the MERaLiON-SpeechEncoder, a foundation model designed for various downstream speech applications. The model is specifically tailored to address speech processing needs in Singapore and Southeast Asia. Currently, it supports mainly English, including Singaporean English. The team is actively expanding the dataset to cover other languages in future releases. The model was pre-trained using 200,000 hours of unlabelled speech data through masked language modelling. Evaluation demonstrates improvements on spontaneous and Singaporean speech benchmarks for speech recognition, while maintaining competitiveness with state-of-the-art models across ten additional tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a special kind of AI model that can help with many different speech-related tasks. It’s designed to work well in Singapore and nearby countries where people speak English or other languages. Right now, the model is mostly trained on English, but the team plans to add more languages soon. To make this model, they used a huge amount of unlabelled speech data and taught it to recognize patterns through a special learning process. When tested, the model did better than expected for recognizing spoken words in Singaporean dialects and other similar tasks. |
