Mountain View, CA, United States of America

Daisy Stanton

USPTO Granted Patents = 8 

 

Average Co-Inventor Count = 4.9

ph-index = 3

Forward Citations = 21(Granted Patents)


Location History:

  • San Francisco, CA (US) (2009 - 2024)
  • Mountain View, CA (US) (2022 - 2024)

Company Filing History:


Years Active: 2009-2024

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8 patents (USPTO):Explore Patents

Title: The Innovative Contributions of Daisy Stanton

Introduction

Daisy Stanton is a prominent inventor based in Mountain View, CA (US). She has made significant contributions to the field of technology, particularly in the area of text-to-speech systems. With a total of 8 patents to her name, her work continues to influence advancements in artificial intelligence and machine learning.

Latest Patents

Stanton's latest patents include groundbreaking technologies such as a neural-network-based text-to-speech model for novel speaker generation. This system allows for the input of text data along with speaker preferences, which can include various speaker characteristics. The machine-learned model processes these preferences to generate audio data that reflects the text spoken by a novel speaker. Another notable patent is her work on variational embedding capacity in expressive end-to-end speech synthesis. This method involves estimating embedding capacity through a deterministic reference encoder and measuring reconstruction loss to optimize audio signal processing.

Career Highlights

Daisy Stanton has established herself as a key figure in her field through her innovative work at Google Inc. Her contributions have not only advanced technology but have also paved the way for future developments in speech synthesis and artificial intelligence.

Collaborations

Stanton has collaborated with notable coworkers such as Eric Dean Battenberg and Soroosh Mariooryad, further enhancing her impact in the industry.

Conclusion

Daisy Stanton's innovative work and numerous patents highlight her significant role in advancing technology, particularly in text-to-speech systems. Her contributions continue to shape the future of artificial intelligence and machine learning.

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