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 …
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 …
Information fusion in attention networks using adaptive and multi-level factorized bilinear pooling for audio-visual emotion recognition
Multimodal emotion recognition is a challenging task in emotion computing as it is quite
difficult to extract discriminative features to identify the subtle differences in human emotions …
difficult to extract discriminative features to identify the subtle differences in human emotions …
Improving convolutional recurrent neural networks for speech emotion recognition
P Meyer, Z Xu, T Fingscheidt - 2021 IEEE Spoken Language …, 2021 - ieeexplore.ieee.org
Deep learning has increased the interest in speech emotion recognition (SER) and has put
forth diverse structures and methods to improve performance. In recent years it has turned …
forth diverse structures and methods to improve performance. In recent years it has turned …
Deep Bispectral Analysis of Conversational Speech Towards Emotional Climate Recognition
G Alhussein, M Alkhodari… - … in Engineering and …, 2023 - ieeexplore.ieee.org
Peers' conversational speech plays a significant role in shaping the emotional climate (EC)
during interactions. Machine-based recognition of EC provides insights into the emotional …
during interactions. Machine-based recognition of EC provides insights into the emotional …
Emotional Climate Recognition in Speech-Based Conversations: Leveraging Deep Bispectral Image Analysis and Affect Dynamics
G Alhussein, M Alkhodari, S Saleem… - Available at SSRN … - papers.ssrn.com
The growing availability and variety of conversational data on multiple platforms have
sparked a rising interest in dynamic emotion recognition. Speech plays a crucial role in …
sparked a rising interest in dynamic emotion recognition. Speech plays a crucial role in …
USING DEEP LEARNING-BASED FRAMEWORK FOR CHILD SPEECH EMOTION RECOGNITION
GN Onwujekwe - 2021 - scholarscompass.vcu.edu
Biological languages of the body through which human emotion can be detected abound
including heart rate, facial expressions, movement of the eyelids and dilation of the eyes …
including heart rate, facial expressions, movement of the eyelids and dilation of the eyes …
Speech Emotion Recognition Using Machine Learning and Deep Learning
AK Thakur, SK Bisoy, P Mishra… - 2024 1st International …, 2024 - ieeexplore.ieee.org
In today's world, understanding and recognizing human emotions are crucial for how we
interact with computers. Exactly finding emotion from speech is a very challenging job. We …
interact with computers. Exactly finding emotion from speech is a very challenging job. We …
Emotieherkenning door Spraakherkenningssoftware
RJ Kersbergen - 2020 - studenttheses.uu.nl
Het belang van het ontwikkelen van automatische spraakherkenning (ASR) wordt steeds
groter. Vooruitgangen in neurale netwerken bieden de mogelijkheid om geavanceerde state …
groter. Vooruitgangen in neurale netwerken bieden de mogelijkheid om geavanceerde state …