{"id":28532321,"url":"https://github.com/predict-idlab/gssp_web_app","last_synced_at":"2026-01-31T05:01:58.226Z","repository":{"id":283738504,"uuid":"620349372","full_name":"predict-idlab/gssp_web_app","owner":"predict-idlab","description":"Web application to acquire picture description speech data according to the GSSP ","archived":false,"fork":false,"pushed_at":"2023-03-29T15:03:40.000Z","size":19617,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-07-07T14:43:35.893Z","etag":null,"topics":["acoustics","experimental-psychology","psychology","speech"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/predict-idlab.png","metadata":{"files":{"readme":"Readme.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-03-28T14:04:49.000Z","updated_at":"2023-03-28T18:55:20.000Z","dependencies_parsed_at":"2025-03-21T21:45:03.792Z","dependency_job_id":"3002da5d-52a0-45f4-99de-f28a24351565","html_url":"https://github.com/predict-idlab/gssp_web_app","commit_stats":null,"previous_names":["predict-idlab/gssp_web_app"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/predict-idlab/gssp_web_app","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/predict-idlab%2Fgssp_web_app","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/predict-idlab%2Fgssp_web_app/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/predict-idlab%2Fgssp_web_app/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/predict-idlab%2Fgssp_web_app/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/predict-idlab","download_url":"https://codeload.github.com/predict-idlab/gssp_web_app/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/predict-idlab%2Fgssp_web_app/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28929862,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-31T04:05:25.756Z","status":"ssl_error","status_checked_at":"2026-01-31T04:02:35.005Z","response_time":128,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["acoustics","experimental-psychology","psychology","speech"],"created_at":"2025-06-09T15:38:11.820Z","updated_at":"2026-01-31T05:01:58.221Z","avatar_url":"https://github.com/predict-idlab.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Speech web app\n\nThis repository contains the web app implementation that was utilized to collect data in order to assess the acoustic properties of the *Ghent Semi-spontaneous Speech Paradigm* (GSSP), a new speech acquisition methodology in which participants were asked to describe images with a constant emotional load. \n\n89 Dutch-speaking participants fulfilled the web-app speech acquisition, which were enrolled through leveraging the researchers' network and the [prolific](https://www.prolific.co/) platform. \n\n**relevant links**:\n- The dataset can be found on [Kaggle](https://www.kaggle.com/datasets/jonvdrdo/gssp-web-app-data)\n- a preprint of the manuscript can be found on [psyarxiv](https://psyarxiv.com/e2qxw)\n- The the GSSP dataset [analysis notebooks](https://github.com/predict-idlab/gssp_analysis)\n\n## Web app structure\n![](img/global_flow.png)\n\nPrior to the the web app its data acquisition, the participants loop through the following steps:\n1. A `Welcome` page, which provides a general overview of the study's purpose\n2. An `Introduction` page, which acquired demographics, together with informed consent\u003cbr\u003eThis page also showed guidelines for the GSSP task.\n3. The `Instructions` page, which provides general instructions for the GSSP task. Specifically:\n    - three [demo](app/static/video/) videos were shown how the task should be performed\n    - the participants were instructed to read aloud the fixed \"Marloes\" text\n4. A 5 minute `Rest` should bring participants into a neutral baseline state\n\n- The First acquisition consists of the Read-aloud `Marloes` task, after which the participants fill in their experienced arousal and valence values during the task.\n![](img/task_flow_marloes.png)\n- Afterwards, 5 PSSG Picture descriptions were acquired (alternating between the [Radboud](app/static/img/Radboud/) and [PiSCES](app/static/img/PiSCES/) image subset). The first shown image always originates from the PiSCES subset. After each image, the participants filled in their experienced arousal and valence values during the task.\n![](img/task_flow.png)\n\nThis was repeated 6 times, follwed by a Final Marloes acquisition, resulting in a total of 7 Marloes samples, 15 Pisces samples and 15 Radboud samples per participant.\n\nThe GSSP is already used in other studies. For example, the [fce_stripped](https://github.com/predict-idlab/gssp_web_app/tree/fce_stripped) branch contains a stripped version of the app in which participants who experienced Adverse Childhood events, filled in this quaestionnaire.\n\n\n---\n### Folder structure\n\n```txt\n└── app\n   ├── API                     \u003c- API endpoints / utlities\n   ├── static\n   │   ├── css\n   │   ├── img                 \u003c- images used in the app\n   │   │   ├── demo\n   │   │   ├── PiSCES\n   │   │   └── Radboud\n   │   ├── _js                 \u003c- javascript files used in the app (audio recording)\n   │   ├── sound               \u003c- sound files used in the app\n   │   └── video               \u003c- demo video of GSSP task\n   └── templates               \u003c- jinja html templates\n```\n\n---\n## Running the web app\n### Via Python\n\nSet first DEPLOY to `False` in the Appconfig class of [app/config.py](app/config.py)\n```bash\n# create a virtual environment\nvirtualenv -p /usr/bin/python3.8 .venv\nsource .venv/bin/activate\n\n# install the required packages\npip install -r requirements.txt\n\n# start the app\npython app/main.py # the app should be accessible on localhost:8080\n\n```\n### Via Docker \n\nMake sure that DEPLOY is set to `True` in the Appconfig class of [app/config.py](app/config.py)\n\n```bash\n# build the image \ndocker build .\n# you should have an output \"sucessfully built \u003cIMAGE_ID\u003e\" on the last line\n\n# test the image\ndocker run -it -p 8081:80 \u003cIMAGE_ID\u003e\n```\n\n---\n\n\u003cp align=\"center\"\u003e\n👤 \u003ci\u003eJonas Van Der Donckt, Mitchel Kappen\u003c/i\u003e\n\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpredict-idlab%2Fgssp_web_app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpredict-idlab%2Fgssp_web_app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpredict-idlab%2Fgssp_web_app/lists"}