Location History:
- New York, NY (US) (2022)
- Mountain View, CA (US) (2023)
Company Filing History:
Years Active: 2022-2023
Title: Min Ma - Innovator in Speech Recognition Technology
Introduction
Min Ma is a prominent inventor based in New York, NY, known for his contributions to the field of speech recognition technology. With a total of two patents to his name, he has made significant strides in developing methods that enhance automatic speech recognition systems.
Latest Patents
Min Ma's latest patents include "Streaming automatic speech recognition with non-streaming model distillation" and "Transliteration for speech recognition training and scoring." The first patent outlines a method for training a streaming automatic speech recognition student model by utilizing a plurality of non-streaming automated speech recognition teacher models. This innovative approach involves generating transcriptions for unlabeled student training utterances and distilling a streaming ASR student model from these teacher models. The second patent focuses on methods and systems for transliteration in speech recognition training. It describes how language examples can be accessed and transliterated to create a training data set, which is then used to generate a language model for improved speech recognition.
Career Highlights
Min Ma is currently employed at Google Inc., where he continues to push the boundaries of speech recognition technology. His work has been instrumental in advancing the capabilities of automated systems, making them more efficient and accurate.
Collaborations
Throughout his career, Min Ma has collaborated with notable colleagues, including Thibault Doutre and Wei Han. These collaborations have fostered an environment of innovation and creativity, contributing to the development of cutting-edge technologies in the field.
Conclusion
Min Ma's contributions to speech recognition technology exemplify the impact of innovative thinking in the tech industry. His patents reflect a commitment to enhancing the functionality and efficiency of automated systems, paving the way for future advancements in this critical area.
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