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Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aphasia, a language disorder primarily caused by a stroke, is traditionally diagnosed using behavioral language tests. However, these tests are time-consuming, require manual interpretation by trained clinicians, suffer from low ecological validity, ...

Exploring Self-Supervised Models for Depressive Disorder Detection: A Study on Speech Corpora.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic detection of depressive disorder from speech signals can help improve medical diagnosis reliability. However, a significant challenge in this field is that most of the available depression datasets are relatively small, which limits the eff...

Research on Tone Enhancement of Mandarin Pitch Controllable Electrolaryngeal Speech Based on Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The deep learning-based electrolaryngeal (EL) voice conversion methods have achieved good results in non-tonal languages. However, the effectiveness in tonal languages, such as Mandarin Chinese (Mandarin), remains suboptimal. The reason may be that t...

EmoNet: Deep Learning-based Emotion Climate Recognition Using Peers' Conversational Speech, Affect Dynamics, and Physiological Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Understanding the emotional dynamics within social interactions is crucial for meaningful interpretation. Despite progress in emotion recognition systems, recognizing the collective emotional climate among peers has been understudied. Addressing this...

Enhancing Word-Level Imagined Speech BCI Through Heterogeneous Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this study, we proposed a novel heterogeneous transfer learning approach named Focused Speech Feature Transfer Learning (FSFTL), aimed at enhancing the performance of electroencephalogram (EEG)-based word-level Imagined Speech (IS) Brain-Computer ...

A unified beamforming and source separation model for static and dynamic human-robot interaction.

JASA express letters
This paper presents a unified model for combining beamforming and blind source separation (BSS). The validity of the model's assumptions is confirmed by recovering target speech information in noise accurately using Oracle information. Using real sta...

[A research on depression recognition based on voice pre-training model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
For the increasing number of patients with depression, this paper proposes an artificial intelligence method to effectively identify depression through voice signals, with the aim of improving the efficiency of diagnosis and treatment. Firstly, a pre...

Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review.

Journal of Alzheimer's disease : JAD
BACKGROUND: Dementia is a general term for several progressive neurodegenerative disorders including Alzheimer's disease. Timely and accurate detection is crucial for early intervention. Advancements in artificial intelligence present significant pot...