Generative Adversarial Network and its Applications to Human Language Processing

Generative adversarial network (GAN) is a new idea for training models, in which a generator and a discriminator compete against each other to improve the generation quality. Recently, GAN has shown amazing results in image generation, but the applications of GAN on text and speech processing are still limited. In this talk, I will demonstrate the applications of GAN on unsupervised abstractive summarization and sentiment controllable chat-bot. I will also talk about the research directions towards unsupervised speech recognition by GAN.

Speaker: Hung-Yi Lee, National Taiwan University

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