Sunnyvale, CA, United States of America

Itay Teller

This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Amazon Technologies, Inc.. Active years: 2024-2025.

USPTO Granted Patents = 2 

% Patents Active = 100.0

Average Co-Inventor Count = 9.5

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2024-2025

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2 patents (USPTO):Explore Patents

Title: Itay Teller: Innovator in Voice Recognition Technology

Introduction

Itay Teller is a prominent inventor based in Sunnyvale, CA, known for his contributions to voice recognition technology. With a total of 2 patents, he has made significant strides in the field, particularly while working at Amazon Technologies, Inc.

Latest Patents

Teller's latest patents include innovative techniques for voice-based user recognition. These techniques involve generating spoken user input embedding data that represents the speech characteristics of a spoken user input. The device processes this data using a machine learning model to create reduced spoken user input embedding data. This data is then compared to user embedding data to determine if the user spoke the input. Another notable patent focuses on detecting whether audio is machine-outputted or non-machine-outputted. This technology allows devices to process audio more effectively by determining its source, ensuring that only relevant audio is processed further.

Career Highlights

Throughout his career, Itay Teller has been instrumental in developing advanced technologies that enhance user interaction with devices. His work at Amazon Technologies, Inc. has positioned him as a key player in the innovation of voice recognition systems.

Collaborations

Teller has collaborated with talented individuals such as Oguz Hasan Elibol and Kian Jamali Abianeh, contributing to the advancement of technology in their respective fields.

Conclusion

Itay Teller's innovative work in voice recognition technology showcases his expertise and commitment to enhancing user experience through advanced machine learning techniques. His contributions continue to shape the future of audio processing and recognition systems.

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