Abstract

A key factor in the success of software is the quality of its documentation. In this talk I will discuss some of the challenges of writing good documentation in the context of software for machine learning. I argue that a documentation-driven approach to the design of software can lead to clearer designs and easier-to-maintain code.

Biography

Daniel Povey completed his PhD at Cambridge University in 2003.  He spent about ten years working for industry research labs (IBM Research and then Microsoft Research), and 7 years as non-tenure-track faculty at Johns Hopkins University; he moved to Beijing, China in November 2019 to join Xiaomi Corporation as Chief Voice Scientist.

He is best known as the principal author and maintainer of the open-source software Kaldi, which is the most popular computer speech recognition software toolkit; the technology of many (possibly most) companies that do speech recognition is based on it, including major corporations like Apple and Amazon.

He is also known for many different contributions to the technology of speech recognition; his papers have over 20,000 citations.