Deep representation learning in speech processing: Challenges, recent advances, and future trends
Research on speech processing has traditionally considered the task of designing hand-
engineered acoustic features (feature engineering) as a separate distinct problem from the …
engineered acoustic features (feature engineering) as a separate distinct problem from the …
AVEC 2019 workshop and challenge: state-of-mind, detecting depression with AI, and cross-cultural affect recognition
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019)'State-of-Mind, Detecting
Depression with AI, and Cross-cultural Affect Recognition'is the ninth competition event …
Depression with AI, and Cross-cultural Affect Recognition'is the ninth competition event …
Survey of deep representation learning for speech emotion recognition
Traditionally, speech emotion recognition (SER) research has relied on manually
handcrafted acoustic features using feature engineering. However, the design of …
handcrafted acoustic features using feature engineering. However, the design of …
An engineering view on emotions and speech: From analysis and predictive models to responsible human-centered applications
The substantial growth of Internet-of-Things technology and the ubiquity of smartphone
devices has increased the public and industry focus on speech emotion recognition (SER) …
devices has increased the public and industry focus on speech emotion recognition (SER) …
Multi-task learning with user preferences: Gradient descent with controlled ascent in pareto optimization
D Mahapatra, V Rajan - International Conference on …, 2020 - proceedings.mlr.press
Abstract Multi-Task Learning (MTL) is a well established paradigm for jointly learning
models for multiple correlated tasks. Often the tasks conflict, requiring trade-offs between …
models for multiple correlated tasks. Often the tasks conflict, requiring trade-offs between …
Personalized multitask learning for predicting tomorrow's mood, stress, and health
While accurately predicting mood and wellbeing could have a number of important clinical
benefits, traditional machine learning (ML) methods frequently yield low performance in this …
benefits, traditional machine learning (ML) methods frequently yield low performance in this …
In search of a robust facial expressions recognition model: A large-scale visual cross-corpus study
Many researchers have been seeking robust emotion recognition system for already last two
decades. It would advance computer systems to a new level of interaction, providing much …
decades. It would advance computer systems to a new level of interaction, providing much …
AVEC 2018 workshop and challenge: Bipolar disorder and cross-cultural affect recognition
The Audio/Visual Emotion Challenge and Workshop (AVEC 2018)" Bipolar disorder, and
cross-cultural affect recognition''is the eighth competition event aimed at the comparison of …
cross-cultural affect recognition''is the eighth competition event aimed at the comparison of …
Multi-modal sarcasm detection and humor classification in code-mixed conversations
Sarcasm detection and humor classification are inherently subtle problems, primarily due to
their dependence on the contextual and non-verbal information. Furthermore, existing …
their dependence on the contextual and non-verbal information. Furthermore, existing …
Learning deep multimodal affective features for spontaneous speech emotion recognition
S Zhang, X Tao, Y Chuang, X Zhao - Speech Communication, 2021 - Elsevier
Recently, spontaneous speech emotion recognition has become an active and challenging
research subject. This paper proposes a new method of spontaneous speech emotion …
research subject. This paper proposes a new method of spontaneous speech emotion …