From search trees to neural nets, a deep dive into natural language processing

<p>We chatted with three guests:</p><p><a href="https://www.linkedin.com/in/migueljette/?originalSubdomain=ca">Miguel Jetté</a>: Head of AI R&D</p><p><a href="https://www.linkedin.com/in/jdongian/">Josh Dong</a>: AI Engineering Manager</p><p><a href="https://www.linkedin.com/in/jennifer-drexler/">Jenny Drexler</a>: Senior Speech Scientist</p><p>When Jette was studying mathematics in the early 2000s, his focus was on computational biology, and more specifically, phylogenetic trees, and DNA sequences. He wanted to understand the evolution of certain traits and the forces that explain why our bones are a certain length or our brains a certain size. As it turned out, the algorithms and techniques he learned in this field mapped very well to the emerging discipline of automatic speech recognition, or ASR. </p><p>During this period, Montreal was emerging as a hotbed for artificial intelligence, and Jette found himself working for Nuance, the company behind the original implementation of Siri. That experience led him to several positions in the world of speech recognition, and he eventually landed at Rev, where he founded the company’s AI department. </p><p>Jette describes Rev as an “Uber for Transcription.” Anyone can sign up for the platform and earn money by listening to audio submitted by clients and transcribing the speech into text. This means the company has a tremendous dataset of raw audio that has been annotated by human beings and, in many cases, assessed a second time by the client. For someone looking to build an AI system that mastered the domain of speech to text, this was a goldmine. </p><p>Jette built the earliest version of Rev’s AI, but it was up to our second guest, Josh Dong, to productize and scale that system. He helped the department transition from older technologies like Perl to more popular languages like Python. He also focused on practical concerns like modularity and reusable components. To combine machine learning and DevOps, Dong added Docker containers and a testing pipeline. If you’re i