UNSUPERVISED PRETRAINING TRANSFERS WELL ACROSS LANGUAGES
UNSUPERVISED PRETRAINING TRANSFERS WELL ACROSS LANGUAGES 1. 论文思路： 作者基于CPC的自监督预训练方法提出了改进版本，解决了原CPC配置中encoder通过batch normalization 泄露信息的问题，并用一层Transformer layer 提升了phoneme 的表征能力。最终得出的主要结论是：通过改进版cpc学习到的表
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相关文章
- 1. [论文] Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages
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- 10. Java NIO Channel to Channel Transfers