NEWS    Jonathan Le Roux gives Plenary Lecture at the JSALT 2020 Summer Workshop

Date released: July 14, 2020


  •  NEWS    Jonathan Le Roux gives Plenary Lecture at the JSALT 2020 Summer Workshop
  • Date:

    July 10, 2020

  • Where:

    Virtual Baltimore, MD

  • Description:

    MERL Senior Principal Research Scientist and Speech and Audio Senior Team Leader Jonathan Le Roux was invited by the Center for Language and Speech Processing at Johns Hopkins University to give a plenary lecture at the 2020 Frederick Jelinek Memorial Summer Workshop on Speech and Language Technology (JSALT). The talk, entitled "Deep Learning for Multifarious Speech Processing: Tackling Multiple Speakers, Microphones, and Languages", presented an overview of deep learning techniques developed at MERL towards the goal of cracking the Tower of Babel version of the cocktail party problem, that is, separating and/or recognizing the speech of multiple unknown speakers speaking simultaneously in multiple languages, in both single-channel and multi-channel scenarios: from deep clustering to chimera networks, phasebook and friends, and from seamless ASR to MIMO-Speech and Transformer-based multi-speaker ASR.

    JSALT 2020 is the seventh in a series of six-week-long research workshops on Machine Learning for Speech Language and Computer Vision Technology. A continuation of the well known Johns Hopkins University summer workshops, these workshops bring together diverse "dream teams" of leading professionals, graduate students, and undergraduates, in a truly cooperative, intensive, and substantive effort to advance the state of the science. MERL researchers led such teams in the JSALT 2015 workshop, on "Far-Field Speech Enhancement and Recognition in Mismatched Settings", and the JSALT 2018 workshop, on "Multi-lingual End-to-End Speech Recognition for Incomplete Data".

  • External Link:

    https://www.clsp.jhu.edu/2020-jsalt-plenary-talks/

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Machine Learning, Speech & Audio