PhD Seminar • Artificial Intelligence — Modelling the Continuum of Emotions in Neural Dialogue SystemsExport this event to calendar

Tuesday, February 19, 2019 — 3:00 PM EST

Nabiha Asghar, PhD candidate
David R. Cheriton School of Computer Science

Most of the existing neural conversational models process natural language primarily on a lexico-syntactic level, thereby ignoring one of the most crucial components of human-to-human dialogue: its affective content. We take a step in this direction by proposing three novel ways to incorporate affective/emotional aspects into long short term memory (LSTM) encoder-decoder neural conversation models: (1) affective word embeddings, which are cognitively engineered, (2) affect-based objective functions that augment the standard cross-entropy loss, and (3) affectively diverse beam search for decoding. Experiments show that these techniques improve the open-domain conversational ability of encoder-decoder networks by enabling them to produce more natural and emotionally rich responses.

Location 
DC - William G. Davis Computer Research Centre
2306C (AI lab)
200 University Avenue West
Waterloo, ON N2L 3G1
Canada

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