Mountain View, CA, United States of America

Liyang Jiang

USPTO Granted Patents = 1 

 

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2022

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1 patent (USPTO):

Title: Liyang Jiang: Innovator in Speech Conversion Technology

Introduction

Liyang Jiang is a prominent inventor based in Mountain View, CA. He has made significant contributions to the field of speech technology, particularly in the area of synthesized data augmentation using voice conversion and speech recognition models. His innovative approach addresses the challenges faced by individuals with atypical speech.

Latest Patents

Liyang Jiang holds a patent for a method that personalizes speech conversion models for target speakers with atypical speech. This patent, titled "Synthesized data augmentation using voice conversion and speech recognition models," outlines a process that involves obtaining a variety of spoken and unspoken training utterances. The method adapts a text-to-speech (TTS) model to synthesize speech that captures the unique characteristics of the target speaker's atypical speech. This innovative approach enhances the training of speech conversion models, allowing for more accurate and personalized speech synthesis.

Career Highlights

Liyang Jiang is currently employed at Google Inc., where he continues to develop cutting-edge technologies in speech recognition and conversion. His work has positioned him as a key player in advancing the capabilities of speech technology, making it more accessible and effective for users with diverse speech patterns.

Collaborations

Throughout his career, Liyang has collaborated with notable colleagues, including Fadi Biadsy and Pedro Jose Moreno Mengibar. These collaborations have fostered an environment of innovation and creativity, leading to advancements in speech technology.

Conclusion

Liyang Jiang's contributions to the field of speech technology exemplify the impact of innovative thinking in addressing real-world challenges. His work not only enhances the capabilities of speech conversion models but also improves the lives of individuals with atypical speech.

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