Papers by Cheng-I Lai
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities (2022.acl-long)
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Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang, Zili Huang, Kushal Lakhotia, Shu-wen Yang, Shuyan Dong, Andy Liu, Cheng-I Lai, Jiatong Shi, Xuankai Chang, Phil Hall, Hsuan-Jui Chen, Shang-Wen Li, Shinji Watanabe, Abdelrahman Mohamed, Hung-yi Lee
| Challenge: | Existing evaluation methods for transfer learning are limited in speech research . authors show that pre-trained models transfer well across multiple tasks . |
| Approach: | They propose a benchmark to evaluate pre-trained models by increasing task diversity and difficulty over SUPERB. |
| Outcome: | The proposed benchmark increases task diversity and difficulty over SUPERB-SG. |
Cross-Modal Discrete Representation Learning (2022.acl-long)
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| Challenge: | a new framework for learning representations from multimodal data is proposed . the proposed framework uses discretized embedding vectors to capture finer levels of granularity . |
| Approach: | They propose a self-supervised representation learning framework that captures finer levels of granularity across different modalities. |
| Outcome: | The proposed representation can capture finer levels of granularity across different modalities . it can be used on cross-modal retrieval tasks without direct supervision . |