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策划，评估和分发提供创新解决方案。Vubble拥有一支由编辑，记者和教师组成的团队，他们策划高质量的在线视频内容，选择最好，最具信息量的视频，并使用Vubble可信度量表评估其真实性，该量表由Vubble在麻省理工学院开发，与尼曼新闻实验室合作，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分类法为内容添加标签，分类法包括“主题”、“基调”和“年级”等类别。 对视频进行分类和分配文本标签需要花费宝贵的编辑时间，并限制了编辑器每天可以处理的视频数量。这种手动流程阻碍了Vubble扩展其业务以满足当前客户日益增长的需求并扩大其客户群的能力。Vubble正在与Seneca合作开发和实施一个自动系统，为视频策展人定制，根据视觉和听觉线索对视频材料进行分类。该系统的实施将使Vubble能够提高生产力，满足现有和新的市场需求，最终实现业务规模的扩大。

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.