Company Filing History:
Years Active: 2017
Title: The Innovations of Daniel Andrés Vásquez Cano
Introduction
Daniel Andrés Vásquez Cano is an accomplished inventor based in Ulm, Germany. He has made significant contributions to the field of phoneme recognition through his innovative patent. His work focuses on enhancing the efficiency and accuracy of neural network structures.
Latest Patents
Daniel holds a patent titled "Downsampling schemes in a hierarchical neural network structure for phoneme recognition." This patent describes a novel approach for phoneme recognition, where a sequence of intermediate output posterior vectors is generated from an input sequence of cepstral features using a first layer perceptron. The intermediate output posterior vectors are downsampled to create a reduced input set for a second layer perceptron. Ultimately, a sequence of final posterior vectors is generated and decoded to determine an output recognized phoneme sequence representative of the input sequence of cepstral features.
Career Highlights
Daniel is currently employed at Nuance Communications, Inc., where he continues to develop cutting-edge technologies in speech recognition. His expertise in neural networks and phoneme recognition has positioned him as a valuable asset in the field.
Collaborations
Some of his notable coworkers include Guillermo Aradilla and Rainer Gruhn, who contribute to the innovative environment at Nuance Communications, Inc.
Conclusion
Daniel Andrés Vásquez Cano's work exemplifies the intersection of technology and innovation in phoneme recognition. His contributions are paving the way for advancements in speech recognition technologies.