Company Filing History:
Years Active: 2016-2018
Title: Innovations by David Pearce in Automatic Speech Recognition
Introduction
David Pearce is an accomplished inventor based in Sunnyvale, CA. He has made significant contributions to the field of automatic speech recognition (ASR) through his innovative patents. With a total of 2 patents, Pearce has developed methods that enhance the efficiency and accuracy of speech recognition systems.
Latest Patents
One of Pearce's latest patents is focused on "Passive training for automatic speech recognition." This invention provides methods and systems for passive training, utilizing a first, speaker-independent model to detect spoken keywords or key phrases. The system then passively trains a second, speaker-dependent model using spoken utterances, which may employ deep neural network (DNN) or convolutional neural network (CNN) techniques. Upon completion of the training, the system switches to the second model for improved detection of spoken keywords or phrases, while also updating parameters based on the spoken utterances.
Another notable patent is "Buffered reprocessing for multi-microphone automatic speech recognition assist." This system includes a buffer for storing sensor data, which represents captured sounds. A processor analyzes this data to produce new parameters, allowing for the separation of clean voice from noise in the acoustic signal. The processed data is then provided to an ASR system, enabling it to operate at a speed faster than real time.
Career Highlights
David Pearce is currently employed at Knowles Electronics, Inc., where he continues to innovate in the field of speech recognition technology. His work has significantly impacted the development of more efficient ASR systems.
Collaborations
Pearce collaborates with talented individuals such as Brian D Clark and Eitan Medina, contributing to advancements in their shared field of expertise.
Conclusion
David Pearce's contributions to automatic speech recognition through his innovative patents demonstrate his expertise and commitment to enhancing technology in this area. His work continues to influence the development of more effective speech recognition systems.