This is a past event.

Dr. Yu Wang, Senior Researcher, Samsung Research, AI Center-Montreal, will present a virtual lecture on Tuesday, March 22, at 1:00 p.m. via Zoom online meeting. Wang has a broad set of research interests spanning deep learning, spoken/natural language understanding, and multi-modal learning.

Talk Title: Data-driven Spoken Language Understanding and Visual Question Answering

Talk Abstract: Spoken language understanding (SLU) and question answering are the most important skills in today’s AI assistants, like Google Assistant, Siri, Alexa, or the Samsung’s Bixby. In order to understand complex spoken human language, an SLU system needs to leverage a large scale of user data for its learning, and perform multi-task concurrently including domain classification, intent detection, and slot tagging. Furthermore, to handle more complex scenarios like visual-based question answering (VQA), a system needs to learn from big data of multi-modalities, like image, spoken language, and even voice signals.

In the first part of this talk, I would like to introduce a universal multi-model deep learning-based SLU system trained from large-scale data, which can perform multiple SLU tasks concurrently, including domain classification, intent detection, and slot tagging.

In the second part of this talk, I would like to present a multi-modal VQA system, which can answer users’ questions based on a given image, by leveraging big data signals from multiple modalities, including image, spoken language, etc.

Read the news blog here: https://blogs.mtu.edu/computing/2022/03/15/cs-faculty-candidate-lecture-yu-wang/