UNSUPERVISED PRETRAINING TRANSFERS WELL ACROSS LANGUAGES
UNSUPERVISED PRETRAINING TRANSFERS WELL ACROSS LANGUAGES 1. 論文思路： 作者基於CPC的自監督預訓練方法提出了改進版本，解決了原CPC配置中encoder通過batch normalization 泄露信息的問題，並用一層Transformer layer 提升了phoneme 的表徵能力。最終得出的主要結論是：通過改進版cpc學習到的表
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相關文章
- 1. [論文] Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages
- 2. Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages論文筆記
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- 10. Java NIO Channel to Channel Transfers