Many audio and video interviews are long and unstructured, and not easily usable as research data. A team from CLARIN’s Czech node has developed a state-of-the-art system that uses speech recognition and other natural language processing technologies designed specifically for oral history archives.
Called ‘Semantic Search – Asking Questions’, this new machine learning technology enables users to easily access oral history archives and engage with them in an intuitive and interactive way. The technology makes it possible to navigate long sequences of oral recordings by providing pre-generated, time-stamped questions that guide users through the content. In addition, a specialised search function enables direct interaction with the content in the video.