Abstract The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling[…]

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Abstract Many AI tasks are best performed by machine learning approaches. Recently, progress in ML has been greatly accelerated by high-performance, easily programmable tools for defining and optimizing deep neural-network architectures.  However, intelligence requires, among[…]

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Abstract Analyzing large volumes of text in various languages and mapping them into a representation that reflects content, rather than form, is one of the great challenges NLP must face. The talk will present UCCA(Universal[…]

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Abstract Natural spoken language interaction between humans and robots has been a long-standing dream of artificial intelligence. Recently, spoken dialog technologies have been applied in real-world man-machine interfaces including smartphone digital assistants, car navigation, voice-controlled[…]

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Multilingual Speech Recognition is a costly AI problem, as each language and even different accents require their own acoustic models to obtain best recognition performance.  Even though they all use the same phoneme symbols, each language[…]

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Abstract To enable naturalistic, context-aware language generation, the underlying models must be flexible but controllable. They must be flexible enough to account for the rich linguistic diversity of data that the model generates and conditions[…]

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Abstract In this talk, I will describe three research problems I have recently worked on and found worth further discussion and investigation in the context of neural machine translation. First, I will discuss whether the[…]

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