Automatic Speech Recognition Transcription Models Explained
Automatic speech recognition, which involves using a computer to transcribe human speech, has always been a classic problem in technology. Classically it fell within the domain of signal processing, but today state of the art methods utilize machine learning to achieve fantastic results. As early…
Nine Must-Read Research Papers from Rev’s AI Experts
Last year, the Speech Team here at Rev began a new tradition: every two weeks, we agreed to read an academic paper and then discuss our thoughts and takeaways over lunch. Our discussions served a few different purposes — to stay up-to-date on the latest…
Rev at Interspeech 2020: Speaker Diarization Q&A
Interspeech 2020 recently invited Rev’s Director of Speech R&D, Miguel Jette, for an upcoming tutorial discussing how Speaker Diarization is used in the industry. The tutorial session is titled “Neural Models for Speaker Diarization in the context of Speech Recognition”. In this quick Q&A session…
The Podcast Challenge: Testing Rev.ai’s Speech Recognition Accuracy
Here on the Rev Speech R&D Team, we are constantly striving to improve Rev.ai’s Automated Speech Recognition (ASR) accuracy. As such, we spend a lot of our time creating test suites for the many different scenarios where our customers use our speech recognition technology. One…
Rev.ai at InterSpeech 2019
INTERSPEECH is always a fascinating conference, with really smart folks, from all over the world, working on a very broad range of applications and research topics. In our daily work, we are typically very focused on the topics that are relevant to us as a…