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Detecting Depression from Voice · Study

WorkDetecting Depression from Voice

Mashrura Tasnim2019

Work2019

Detecting Depression from Voice

Mashrura Tasnim · Eleni Stroulia

48 citations·0/0 files stored·Lecture notes in computer science

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Emotion and Mood Recognition Speech Recognition and Synthesis Mental Health via Writing

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References

2014StudentLife 2013AVEC 2013 2017AVEC 2017 2010Detection of Clinical Depression in Adolescents’ Speech During Family Interactions 2018Automated depression analysis using convolutional neural networks from speech 2007Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech 2013Vocal biomarkers of depression based on motor incoordination 2017Topic Modeling Based Multi-modal Depression Detection

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Papers that cite the same references — the relational fallback while embeddings are still backfilling.

2022Automatic depression recognition by intelligent speech signal processing: A systematic surveyarticle · 7 shared references 2021A hierarchical depression detection model based on vocal and emotional cuesarticle · 5 shared references 2023Spatial–Temporal Feature Network for Speech-Based Depression Recognitionarticle · 5 shared references 2024Two-Stage Temporal Modelling Framework for Video-Based Depression Recognition Using Graph Representationarticle · 5 shared references 2018Bipolar Disorder Recognition via Multi-scale Discriminative Audio Temporal Representationother · 5 shared references 2021Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speechother · 4 shared references

Details

Year2019

Typeother

Published2019-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations48

Files0 public / 0

ShelfEmotion and Mood Recognition

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doi10.1007/978-3-030-18305-9_47

openalex_workW2946585360

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