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Milpitas, CA, United States of America

Antoine Jean Bruguier

This inventor holds 16 USPTO granted patents and 3 published patent applications and 4 EPO patents, primarily in Speech Recognition Technology. Top assignees: Google Inc., Asml Netherlands B.v.. Active years: 2013-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Antoine Jean Bruguier. Retrieved from https://idiyas.com/inventor/antoine-jean-bruguier

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 16 

% Patents Active = 87.5

 

Average Co-Inventor Count = 3.9

ph-index = 4

Forward Citations = 46(Granted Patents)


Company Filing History:

goldMedal11 out of 33,987 
 
Google Inc.
 patents
silverMedal5 out of 5,076 
 
Asml Netherlands B.v.
 patents

Years Active: 2013-2026

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Areas of Expertise:
Speech Recognition
End-to-End Models
Contextual Biasing
Neural Network Compression
Phoneme-Based Contextualization
Cross-Lingual Recognition
Harmonic Resist Model
Calibration Pattern Selection
Entity Pronunciations
Streaming ASR
16 patents (USPTO):Explore Patents
1. 12620390 - Flickering reduction with partial hypothesis re-ranking for streaming ASR (2026-05-05),
2. 12073824 - Two-pass end to end speech recognition (2024-08-27),
3. 11948062 - Compressed recurrent neural network models (2024-04-02),
4. 11942076 - Phoneme-based contextualization for cross-lingual speech recognition in end-to-end models (2024-03-26),
5. 11664021 - Contextual biasing for speech recognition (2023-05-30),
6. 11270687 - Phoneme-based contextualization for cross-lingual speech recognition in end-to-end models (2022-03-08),
7. 11217231 - Contextual biasing for speech recognition using grapheme and phoneme data (2022-01-04),
8. 10878319 - Compressed recurrent neural network models (2020-12-29),
9. 10484319 - Date and/or time resolution (2019-11-19),
10. 10277543 - Date and/or time resolution (2019-04-30),
11. 10152965 - Learning personalized entity pronunciations (2018-12-11),
12. 9588439 - Information matrix creation and calibration test pattern selection based on computational lithography model parameters (2017-03-07),
13. 8942463 - Harmonic resist model for use in a lithographic apparatus and a device manufacturing method (2015-01-27),
14. 8887105 - Calibration pattern selection based on noise sensitivity (2014-11-11),
15. 8682059 - Harmonic resist model for use in a lithographic apparatus and a device manufacturing method (2014-03-25),

Certainly! Here is an article about the inventor Antoine Jean Bruguier based on the provided data:

Title: Unveiling the Innovations of Antoine Jean Bruguier in Milpitas, CA

Introduction:

Antoine Jean Bruguier, a brilliant inventor hailing from Milpitas, CA, has made significant contributions to the field of technology with a total of 14 patents under his name.

Latest Patents:

One of his latest patents includes "Compressed recurrent neural network models," focusing on implementing a compressed recurrent neural network with various intricate layers and weight matrices. Another notable patent is "Phoneme-based contextualization for cross-lingual speech recognition in end-to-end models," showcasing his expertise in speech recognition technologies.

Career Highlights:

During his illustrious career, Antoine Jean Bruguier has worked with renowned companies such as Google Inc. and ASML Netherlands B.V., where he honed his skills and brought his inventive ideas to life.

Collaborations:

In his professional journey, Antoine Jean Bruguier has collaborated with esteemed coworkers like Rohit Prakash Prabhavalkar and Wenjin Shao, fostering a culture of innovation and teamwork in his projects.

Conclusion:

Through his groundbreaking patents and successful collaborations, Antoine Jean Bruguier has left an indelible mark in the world of technology, showcasing his prowess as a visionary inventor dedicated to pushing the boundaries of what is possible.

If you need more information or details, feel free to ask!

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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