Capturing Mismatch between Textual and Acoustic Emotion Expressions for Mood Identification in Bipolar Disorder

Niu, Minxue; Romana, Amrit; Jaiswal, Mimansa; McInnis, Melvin G.; Provost, Emily Mower

doi:10.21437/interspeech.2023-1990

Interspeech 2023 2023

DOI: 10.21437/interspeech.2023-1990

|View full text |Cite

Capturing Mismatch between Textual and Acoustic Emotion Expressions for Mood Identification in Bipolar Disorder

Minxue Niu¹,

Amrit Romana²,

Mimansa Jaiswal³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Responsible development of clinical speech AI: Bridging the gap between clinical research and technology

Berisha,

Liss

2024

npj Digit. Med.

View full text Add to dashboard Cite

This perspective article explores the challenges and potential of using speech as a biomarker in clinical settings, particularly when constrained by the small clinical datasets typically available in such contexts. We contend that by integrating insights from speech science and clinical research, we can reduce sample complexity in clinical speech AI models with the potential to decrease timelines to translation. Most existing models are based on high-dimensional feature representations trained with limited sample sizes and often do not leverage insights from speech science and clinical research. This approach can lead to overfitting, where the models perform exceptionally well on training data but fail to generalize to new, unseen data. Additionally, without incorporating theoretical knowledge, these models may lack interpretability and robustness, making them challenging to troubleshoot or improve post-deployment. We propose a framework for organizing health conditions based on their impact on speech and promote the use of speech analytics in diverse clinical contexts beyond cross-sectional classification. For high-stakes clinical use cases, we advocate for a focus on explainable and individually-validated measures and stress the importance of rigorous validation frameworks and ethical considerations for responsible deployment. Bridging the gap between AI research and clinical speech research presents new opportunities for more efficient translation of speech-based AI tools and advancement of scientific discoveries in this interdisciplinary space, particularly if limited to small or retrospective datasets.

show abstract

Responsible development of clinical speech AI: Bridging the gap between clinical research and technology

Berisha,

Liss

2024

npj Digit. Med.

View full text Add to dashboard Cite

show abstract

Expressed Emotion in Families of People With Dementia: A Review of Scale-Based Measures

Liu,

Mo,

Takiue

et al. 2024

J Gerontol Nurs

View full text Add to dashboard Cite

Purpose: Research on the concept of expressed emotion (EE) has expanded in recent years but its role in dementia still requires elucidation. Understanding the role of EE in the dementia context could help in the development of appropriate interventions. Method: The current review synthesized relevant literature to investigate the prevalence and correlates of EE status in families of people with dementia. A comprehensive search of four databases from inception to 2022 produced 2,683 papers; 18 studies met inclusion criteria. Results: The use of EE criteria differed not only across cultural contexts, but even within the same cultural context. Overall, the prevalence of EE in families with dementia compared with other psychiatric conditions was not high. Conclusion: Specific changes in EE over time remain to be explored, and findings emphasize the need to carefully discriminate High EE status based on the cultural background of family members with dementia. [ Journal of Gerontological Nursing, 50 (2), 17–25.]

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Capturing Mismatch between Textual and Acoustic Emotion Expressions for Mood Identification in Bipolar Disorder

Cited by 2 publications

References 0 publications

Responsible development of clinical speech AI: Bridging the gap between clinical research and technology

Responsible development of clinical speech AI: Bridging the gap between clinical research and technology

Expressed Emotion in Families of People With Dementia: A Review of Scale-Based Measures

Contact Info

Product

Resources

About