About
7
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Introduction
Hi, I am a PhD candidate at the Speech& Behavioral Signal Processing Lab, University of New South Wales. My research interests include affective computing, emotion recognition, machine learning, deep learning and uncertainty modelling. I am currently working on the field of speech emotion prediction. I feel there are lots of unknown mysteries to be discovered in our world and the world of science. I will always keep my mind open and broad to see, to listen, to feel and to learn.
Education
September 2020 - February 2024
UNSW Sydney
Field of study
- Signal Processing, Electrical Engineering
June 2016 - January 2020
Publications
Publications (7)
Despite of efforts made to model emotion ambiguity and develop ambiguity aware emotion prediction systems, there is a need for a quantitative and interpretable measure of the accuracy of such systems, regardless of recent advances in representing emotion ambiguity through probability distributions. In this paper, we propose a novel measure called t...
A number of machine learning applications involve time series prediction, and in some cases additional information about dynamical constraints on the target time series may be available. For instance, it might be known that the desired quantity cannot change faster than some rate or that the rate is dependent on some known factors. However, incorpo...
There is growing interest in affective computing for the representation and prediction of emotions along ordinal scales. However, the term ordinal emotion label has been used to refer to both absolute notions such as low or high arousal, as well as relation notions such as arousal is higher at one instance compared to another. In this paper, we int...
People perceive emotions via multiple cues, predominantly speech and visual cues, and a number of emotion recognition systems utilize both audio and visual cues. Moreover, the perception of static aspects of emotion (speaker's arousal level is high/low) and the dynamic aspects of emotion (speaker is becoming more aroused) might be perceived via dif...
There is growing interest in affective computing for the representation and prediction of emotions along ordinal scales. However, the term ordinal emotion label has been used to refer to both absolute notions such as low or high arousal, as well as relation notions such as arousal is higher at one instance compared to another. In this paper, we int...
