YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.
The company says user tests indicate that the feature significantly improves the experience of the deaf and hard of hearing (and anyone who needs to keep the volume down). “Machine learning is giving people like me that need accommodation in some situations the same independence as others,” says Liat Kaver, a product manager at YouTube who is deaf.
Indeed, YouTube’s project is one of a variety that are creating new accessibility tools by building on progress in the power and practicability of machine learning. The computing industry has been driven to advance software that can interpret images, text, or sound primarily by the prospect of profits in areas such as ads, search, or cloud computing. But software with some ability to understand the world has many uses.