{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/openxbow-introducing-the-passau-open-source","title":"openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit","arxiv_id":"1605.06778","date":"2016-05-22","proceeding":null,"authors":["Maximilian Schmitt","Björn W. Schuller"],"abstract":"We introduce openXBOW, an open-source toolkit for the generation of\nbag-of-words (BoW) representations from multimodal input. In the BoW principle,\nword histograms were first used as features in document classification, but the\nidea was and can easily be adapted to, e.g., acoustic or visual low-level\ndescriptors, introducing a prior step of vector quantisation. The openXBOW\ntoolkit supports arbitrary numeric input features and text input and\nconcatenates computed subbags to a final bag. It provides a variety of\nextensions and options. To our knowledge, openXBOW is the first publicly\navailable toolkit for the generation of crossmodal bags-of-words. The\ncapabilities of the tool are exemplified in two sample scenarios:\ntime-continuous speech-based emotion recognition and sentiment analysis in\ntweets where improved results over other feature representation forms were\nobserved.","url_abs":"http://arxiv.org/abs/1605.06778v1","url_pdf":"http://arxiv.org/pdf/1605.06778v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"openxbow-introducing-the-passau-open-source","repo_url":"https://github.com/openXBOW/openXBOW","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"document-classification","task_name":"Document Classification"},{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1605.06778","atlas_url":"https://app.syntology.ai/?focus=1605.06778","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}