Unsupervised personalization of an emotion recognition system: The unique properties of the externalization of valence in speech
The prediction of valence from speech is an important, but challenging problem. The
expression of valence in speech has speaker-dependent cues, which contribute to …
expression of valence in speech has speaker-dependent cues, which contribute to …
Fearless steps challenge (fs-2): Supervised learning with massive naturalistic apollo data
The Fearless Steps Initiative by UTDallas-CRSS led to the digitization, recovery, and
diarization of 19,000 hours of original analog audio data, as well as the development of …
diarization of 19,000 hours of original analog audio data, as well as the development of …
[PDF][PDF] The DiCOVA 2021 Challenge: an encoder-decoder approach for COVID-19 recognition from coughing audio
G Deshpande, BW Schuller - 2021 - opus.bibliothek.uni-augsburg.de
This paper presents the automatic recognition of COVID-19 from coughing. In particular, it
describes our contribution to the DiCOVA challenge–Track 1, which addresses such cough …
describes our contribution to the DiCOVA challenge–Track 1, which addresses such cough …
Exploring skin conductance features for cross-subject emotion recognition
Human emotion recognition is an important research problem in various fields like human-
computer interactions, learning, marketing etc. Physiological signals like galvanic skin …
computer interactions, learning, marketing etc. Physiological signals like galvanic skin …
Analysis of Respiratory Health Indicators in Speech-Breathing-Patterns
G Deshpande, BW Schuller - 2024 32nd European Signal …, 2024 - ieeexplore.ieee.org
Speech production and respiration co-occur, and hence, speech signals encode information
regarding an individual's respiratory health. Disorders within the respiratory tract often …
regarding an individual's respiratory health. Disorders within the respiratory tract often …
Analysing Breathing Patterns in Reading and Spontaneous Speech
This paper focuses on the time and phase-domain analysis of speech signals to extract
breathing patterns. The speech signals under investigation fall into two categories: reading …
breathing patterns. The speech signals under investigation fall into two categories: reading …
Breathing patterns in speech: discovering markers of health
G Deshpande - 2024 - opus.bibliothek.uni-augsburg.de
This thesis delves into the realm of speech representation and deep learning techniques to
extract breathing patterns from speech signals. Breathing patterns—the signals generated …
extract breathing patterns from speech signals. Breathing patterns—the signals generated …
[PDF][PDF] Role of emotion words in detecting emotional valence from speech
VS Viraraghavan, RD Gavas… - SMM20, Workshop on …, 2020 - isca-archive.org
An important task in several wellness applications is detection of emotional valence from
speech. Two types of features of speech signals are used to detect valence: acoustic …
speech. Two types of features of speech signals are used to detect valence: acoustic …
Unsupervised Personalization and Deep Uncertainty Modeling for Speech Emotion Recognition
KSHS Murthy - 2021 - search.proquest.com
Robust, reliable and generalizable speech emotion recognition (SER) systems have wide
application in areas such as healthcare, security and defense. These areas require mission …
application in areas such as healthcare, security and defense. These areas require mission …