Papers with cross-language transfer learning
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian (2022.lrec-1)
Copied to clipboard
| Challenge: | Hungarian is spoken by 15 million people, yet, easily accessible Automatic Speech Recognition (ASR) benchmark datasets are practically unavailable. |
| Approach: | They propose to use a subset of the BEA spoken Hungarian database to assess ASR, primarily for conversational AI applications. |
| Outcome: | The proposed framework achieves 45% reduction in recognition error rate compared to classical approach without external language model or additional supervised data. |
The Less the Merrier? Investigating Language Representation in Multilingual Models (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Multilingual models can be used to integrate multiple languages into one model and use cross-language transfer learning to improve performance for different NLP tasks. |
| Approach: | They propose to include languages in popular multilingual models and to use cross-language transfer learning to improve performance for different NLP tasks. |
| Outcome: | The proposed models perform better on downstream tasks for seen and unseen languages than community-centered models for low-resource languages. |