Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification

Understand

In recent years great success has been achieved in sentiment classification for English, thanks in part to the availability of copious annotated resources.

• Unfortunately, most languages do not enjoy such an abundance of labeled data.
• To tackle the sentiment classification problem in low-resource languages without adequate annotated data, we propose an Adversarial Deep Averaging Network (ADAN) to transfer the knowledge learned from labeled data on a resource-rich source language to low-resource languages where only unlabeled data exists.
• ADAN has two discriminative branches: a sentiment classifier and an adversarial language discriminator.