PeopleofSuperintelligence

Researcher

Elizabeth Shriberg

Also known as E. Shriberg, Elizabeth E. Shriberg, Elizabeth Ellen Shriberg

Elizabeth Shriberg is a speech and language researcher whose work connects prosody and disfluency modeling with automatic speech understanding and speaker recognition. She earned a linguistics degree from Harvard and master’s and PhD degrees in cognitive science from Berkeley; her 1994 dissertation examined spontaneous-speech disfluencies. Between 1998 and 2004, she coauthored research on speaker verification, disfluency acoustics, and direct prosody modeling, and she became an ISCA Fellow in 2009 and an SRI Fellow in 2010. She later leads Ellipsis Health’s Machine Learning team as Chief Science Officer after research roles at SRI, Microsoft, and Amazon Alexa. As of October 2026, she is a Senior Advisor at Nūr, guiding vocal signal interpretation and machine-learning validation.

Links
LinkedIn

Timeline

  1. 1994

    A dissertation on disfluencies

    She holds a linguistics degree from Harvard and master’s and PhD degrees in cognitive science from Berkeley. Her 1994 Berkeley dissertation analyzes disfluencies in spontaneous speech.

  2. 1998–2004

    Prosody and speaker recognition

    In 1998, she coauthors a speaker-verification study that reports prosody modeling improves a Gaussian-mixture system’s verification performance by 10%. Her 1999 study shows that disfluency affects segment durations, intonation, voice quality, vowel quality, and coarticulation, with applications in speech recognition. In 2004, she and Andreas Stolcke describe direct prosody models for sentence boundaries, disfluencies, dialog acts, emotion, speaker recognition, and word recognition.

  3. 2009

    An ISCA Fellowship

    She receives the 2009 ISCA Fellowship for research on disfluencies, prosody in speech understanding, and higher-level features in speaker recognition.

  4. 2010

    An SRI Fellowship

    In 2010, SRI names her one of three Fellows selected by its committee.

  5. 2022

    Voice-based depression screening

    In 2022, a feasibility study explores a machine-learning smartphone app for detecting depression and anxiety in a generally senior population.

  6. By 2024

    Chief Science Officer at Ellipsis

    By 2024, she joins Ellipsis Health as Chief Science Officer in charge of its Machine Learning team. Her earlier roles include Principal Scientist at SRI International and Microsoft, then Senior Principal Scientist in speech and health at Amazon’s Alexa AI.

  7. December 2024

    Depression classification by speech length

    In December 2024, she coauthors a preprint on how speech-input length affects speaker-independent depression classification.

  8. As of October 2026

    Senior Advisor at Nūr

    As of October 2026, she is a Senior Advisor at Nūr, guiding vocal signal interpretation, machine-learning validation, and the integration of human-behavior research into AI systems.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. Preliminaries to a theory of speech disfluencies old.filledpause.org. Checked 19 October 2026.
  2. The Ellipsis Health journey: A global solution inspired by a personal struggle ellipsishealth.com. Checked 19 October 2026.
  3. Modeling Dynamic Prosodic Variation for Speaker Verification - SRI sri.com. Checked 19 October 2026.
  4. ICPhS-14 Abstract: Shriberg, Elizabeth E. internationalphoneticassociation.org. Checked 19 October 2026.
  5. ISCA Archive - Direct modeling of prosody: an overview of applications in automatic speech processing isca-archive.org. Checked 19 October 2026.
  6. ISCA - ISCA Fellow Program isca-speech.org. Checked 19 October 2026.
  7. SRI International Announces Recipients of Its 2010 Fellowship Award prnewswire.com. Checked 19 October 2026.
  8. Feasibility of a Machine Learning-Based Smartphone Application in Detecting Depression and Anxiety in a Generally Senior Population frontiersin.org. Checked 19 October 2026.
  9. Nūr AI Voice Coach | Improve Communication mynur.ai. Checked 19 October 2026.
  10. Optimizing Speech-Input Length for Speaker-Independent Depression Classification arxiv.org. Checked 19 October 2026.