Incremental Video Categorization Using Audio and Video Features

Vubble由经验丰富的媒体高管Tessa Sproule和Katie MacGuire于2014年成立，是一家媒体和教育技术公司，为值得信赖的数字视频管理，评估和分发构建并提供创新解决方案。Vubble拥有一支由编辑、记者和教师组成的团队，他们负责策划高质量的在线视频内容，选择最好、最翔实的视频，并使用Vubble可信度测量仪评估其真实性，该测量仪是Vubble在麻省理工学院与尼曼新闻实验室合作开发的，于2017年2月。Vubble的编辑通过他们的“数据标签”过程为每个视频添加结构化数据——他们使用他们的分类法来标记内容，其中包括“主题”、“语气”和“年级水平”等类别。

Incorporated by seasoned media executives Tessa Sproule and Katie MacGuire in 2014, Vubble is a media and education technology company that builds and offers innovative solutions for trustworthy digital video curation, assessment, and distribution. Vubble has a team of editors, journalists and teachers who curate quality online video content, selecting the best, most informative videos and assess their veracity using the Vubble Credibility Meter, which Vubble developed at MIT, in collaboration with the Nieman Journalism Lab, in February 2017. Vubble's editors add structured data to each video, through their 'data labelling' process-they tag content using their taxonomy, which includes categories such as 'topic', 'tone' and 'grade level'. Categorization and assignment of textual labels to the videos takes valuable editorial time and limits the number of videos an editor can process in a day. This manual process is a hindrance to Vubble's ability to scale its operations to meet the increasing needs of its current customers and grow its customer base. Vubble is partnering with Seneca to develop and implement an automatic system, customized for video curators, to categorize video material based on both visual and audio cues. Implementation of the system will enable Vubble to increase its productivity and address existing and new market demand, ultimately enabling the scaling of its business.