Systematic review of digital phenotyping and machine learning in psychosis spectrum illnesses
Background Digital phenotyping is the use of data from smartphones and wearables
collected in situ for capturing a digital expression of human behaviors. Digital phenotyping …
collected in situ for capturing a digital expression of human behaviors. Digital phenotyping …
[HTML][HTML] A review of generalizable transfer learning in automatic emotion recognition
K Feng, T Chaspari - Frontiers in Computer Science, 2020 - frontiersin.org
Automatic emotion recognition is the process of identifying human emotion from signals
such as facial expression, speech, and text. Collecting and labeling such signals is often …
such as facial expression, speech, and text. Collecting and labeling such signals is often …
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 …
Improving cross-corpus speech emotion recognition with adversarial discriminative domain generalization (ADDoG)
J Gideon, MG McInnis… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Automatic speech emotion recognition provides computers with critical context to enable
user understanding. While methods trained and tested within the same dataset have been …
user understanding. While methods trained and tested within the same dataset have been …
Privacy enhanced multimodal neural representations for emotion recognition
M Jaiswal, EM Provost - Proceedings of the AAAI Conference on …, 2020 - ojs.aaai.org
Many mobile applications and virtual conversational agents now aim to recognize and adapt
to emotions. To enable this, data are transmitted from users' devices and stored on central …
to emotions. To enable this, data are transmitted from users' devices and stored on central …
[HTML][HTML] Voice analysis for neurological disorder recognition–a systematic review and perspective on emerging trends
Quantifying neurological disorders from voice is a rapidly growing field of research and
holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup …
holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup …
Smartphone sensing of social interactions in people with and without schizophrenia
Social impairment is a cardinal feature of schizophrenia spectrum disorders (SZ). Smaller
social network size, diminished social skills, and loneliness are highly prevalent. Existing …
social network size, diminished social skills, and loneliness are highly prevalent. Existing …
Exploiting vocal tract coordination using dilated cnns for depression detection in naturalistic environments
Depression detection from speech continues to attract significant research attention but
remains a major challenge, particularly when the speech is acquired from diverse …
remains a major challenge, particularly when the speech is acquired from diverse …
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) …
Investigation of speech landmark patterns for depression detection
The massive and growing burden imposed on modern society by depression has motivated
investigations into early detection through automated, scalable and non-invasive methods …
investigations into early detection through automated, scalable and non-invasive methods …