In academic libraries, speech-to-text tools can support access, discovery, and preservation activities. They may be used to generate transcripts for recorded lectures, oral histories, interviews, archival film collections, and more, improving accessibility for users who are deaf or hard of hearing and enabling text-based searching of audio and video collections.
The newest post in our AI Tools for Academic Libraries series explores five AI-enabled speech-to-text models, evaluating their user interfaces, hosting environments, customizability and more — applying the same testing process used in the initial stages of OCUL's Audio to Text project.
Read the full post: AI Tools for Academic Libraries: AI Speech-to-Text Models
AI Tools for Academic Libraries is part of the OCUL AI and Machine Learning Initiative. The blog series is a collaboration between OCUL and Choice, a publishing unit of the Association of College and Research Libraries, and is hosted on Choice's LibTech Insights content channel that examines the day-to-day impact of library and education tech on academic librarians.