Kyle Roth

I'm a speech scientist at Cobalt Speech & Language, a company that designs custom speech recognition, text-to-speech, and dialogue models. While at Cobalt I've worked on some neat projects, including language modeling for recognizing air traffic control speech and creating an online training system for ASR models. I am currently in the process of applying to PhD programs in computer science, to start in 2021. See the Research section for some of the areas of machine learning that I find fascinating.

I love using math and code to solve complex problems. I wrote my first lines of Python in 2012, and it was there that I developed a love for software. I graduated from BYU with a BS in Applied and Computational Mathematics (ACME) with an emphasis in linguistics, though I also minored in computer science.

During my undergrad I interned with Cobalt Speech (my current employer), as well as Emergent Trading, an automated trading firm that made the news for reporting a problem in a Eurodollar exchange rule that unfairly favored larger competitors. (I developed the analysis tools that were used to track the issue down and determine how our opponent was taking advantage of the rule.)


Around the web I'm known by the username kylrth. I prefer to be contacted through the Matrix protocol (

Matrix  /  Email  /  Twitter  /  Github  /  LinkedIn


My first foray into ML research was when I received a grant to apply a variable-order CRF model to a morphological parsing task in Basque, achieving 71.3% accuracy. A few months later I started working with the computational photonics group at CamachoLab, where I worked to simulate photonic components using DNNs as replacements for expensive FDTD simulations when designing chip components.

Here are some of my current interests:

  • machine translation
  • the relationship between language and representation
  • developing better theories about how networks learn (see "An Introduction to Circuits")
  • end-to-end models for speech recognition
  • attention mechanisms (see this literature review I wrote on the subject)

My open source work generally ends up on GitHub.

SLURM logo


SLURM_gen makes it easy to generate and handle arbitrarily-sized datasets on a SLURM HPC environment. I used this tool during my undergrad while working on computational photonics research. (I used the BYU supercomputer to generate FDTD simulations, which were then used as training data for the neural network model.)

Twitter image created by Shawn Campbell. See attribution below.


An n-gram text generator that handles punctuation and end-of-tweet along with the words. It tries to use hashtags, @-mentions, and URLs correctly.

Here you go Jared.

Site created from Jon Barron's template with some suspicious similarities to Thomas Wolf's site.

Twitter image created by Shawn Campbell and used according to the terms of the CC BY 2.0 license.