Predicting depression from acoustic features of speech using a Convolutional Neural Network.
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Updated
Oct 29, 2018 - Python
Predicting depression from acoustic features of speech using a Convolutional Neural Network.
The first asian machine learning in Jeju Island, South Korea - Project
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😔 😞 😣 😖 😩 Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"
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A mental health quiz app to help individuals check in with themselves.
Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction (ICANN 2021)
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A Scraper that scrapes '#depression' tweets daily powered by GitHub action and snscrape (stopped at June 30,2023)
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A visual representation of depressive thoughts.
The Harmony Python library: a research tool for psychologists to harmonise data and questionnaire items. Open source.
Self-Diagnosis Tool for Depression
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Depression Detection from Speech
Our project is a mental health companion intended to improve one’s outlook with the power of positive thinking. This app uses Twilio to send messages of encouragement to a phone number you provide after logging in.
Sentiment analysis for depression based on Twitter posts 📊 [finished]
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