Company Filing History:
Years Active: 2015-2018
Title: The Innovative Contributions of Daniel Almendro Barreda
Introduction
Daniel Almendro Barreda is a notable inventor based in London, GB. He has made significant contributions to the field of voice activity detection and language identification technologies. With a total of 5 patents to his name, Barreda's work has had a considerable impact on the way speech is processed in digital systems.
Latest Patents
One of Barreda's latest patents is focused on voice activity detection (VAD) for a coded speech bitstream without decoding. This innovative system, method, and computer program product are designed to detect voice activity within a digitally encoded bitstream. The technology includes a parameter extraction module that extracts parameters from a sequence of coded frames containing speech. A VAD classifier evaluates each coded frame based on bitstream coding parameter classification features, ultimately outputting a VAD decision that indicates whether speech is present.
Another significant patent by Barreda is a system and method for compressed domain language identification. This invention involves receiving a bitstream of packets and classifying each packet into speech or non-speech using compressed domain voice activity detection. The technology also includes extracting a pseudo-cepstral representation from the detected speech packets and generating a sequence of multi-frames for real-time processing by a deep neural network trained for specific target languages.
Career Highlights
Daniel Almendro Barreda is currently employed at Nuance Communications, Inc., where he continues to develop cutting-edge technologies in speech processing. His work has been instrumental in advancing the capabilities of voice recognition systems.
Collaborations
Barreda has collaborated with notable colleagues such as Dushyant Sharma and Patrick A Naylor, contributing to various projects that enhance the field of speech technology.
Conclusion
Daniel Almendro Barreda's innovative patents and contributions to voice activity detection and language identification demonstrate his expertise and commitment to advancing technology in this field. His work continues to influence the development of more efficient speech processing systems.