Mountain View, CA, United States of America

Chris Leggetter


Average Co-Inventor Count = 5.0

ph-index = 2

Forward Citations = 80(Granted Patents)


Company Filing History:


Years Active: 2006-2009

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3 patents (USPTO):Explore Patents

Title: Innovations in Speech Recognition by Chris Leggetter

Introduction

Chris Leggetter is an accomplished inventor based in Mountain View, CA. He has made significant contributions to the field of speech recognition technology. With a total of 3 patents to his name, Leggetter's work focuses on enhancing the efficiency and accuracy of speech recognition systems.

Latest Patents

Leggetter's latest patents include the "Selective Multi-Pass Speech Recognition System and Method" and the "Adaptive Multi-Pass Speech Recognition System." The first patent describes a method and apparatus where an input device receives spoken input. A processor performs a first pass speech recognition technique, generating results that include alternative speech expressions with assigned scores indicating their accuracy. The processor then selectively executes a second pass based on these results, improving recognition speed and accuracy. The second patent follows a similar approach but also identifies characteristics of the spoken input, such as the speaker's gender or the type of telephone used. This allows for a more tailored second pass technique, further enhancing performance.

Career Highlights

Chris Leggetter is currently employed at Nuance Communications, Inc., a leader in AI-driven speech recognition solutions. His work at Nuance has positioned him at the forefront of innovation in this rapidly evolving field.

Collaborations

Throughout his career, Leggetter has collaborated with notable colleagues, including Hy Murveit and Ashvin Kannan. These partnerships have contributed to the development of advanced speech recognition technologies.

Conclusion

Chris Leggetter's innovative contributions to speech recognition technology have significantly impacted the industry. His patents reflect a commitment to improving the efficiency and accuracy of speech recognition systems.

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