Company Filing History:
Years Active: 2025
Title: The Innovations of David Rybach
Introduction
David Rybach is an accomplished inventor based in Mountain View, California. He is known for his significant contributions to the field of automatic speech recognition (ASR). With a focus on enhancing the efficiency and accuracy of speech recognition technologies, Rybach has made a notable impact in the tech industry.
Latest Patents
Rybach holds a patent for a groundbreaking innovation titled "Two-pass end to end speech recognition." This patent describes a two-pass automatic speech recognition model that can perform streaming on-device ASR to generate a text representation of utterances captured in audio data. The first-pass portion of the ASR model utilizes a recurrent neural network transformer (RNN-T) decoder to generate streaming candidate recognitions. The second-pass portion revises these recognitions and generates a text representation using a listen attend spell (LAS) decoder. This innovative approach includes a shared encoder that connects both the RNN-T and LAS decoders, enhancing the overall performance of the ASR system.
Career Highlights
David Rybach is currently employed at Google Inc., where he continues to develop and refine technologies related to speech recognition. His work at Google has positioned him as a key player in advancing the capabilities of ASR systems. Rybach's dedication to innovation is evident in his patent and ongoing projects.
Collaborations
Throughout his career, Rybach has collaborated with talented individuals in the field, including Tara N Sainath and Ruoming Pang. These collaborations have fostered a creative environment that encourages the development of cutting-edge technologies.
Conclusion
David Rybach's contributions to the field of automatic speech recognition exemplify the spirit of innovation. His patent for two-pass end-to-end speech recognition showcases his commitment to improving technology that impacts everyday communication. Rybach's work at Google continues to influence the future of speech recognition systems.