Company Filing History:
Years Active: 2011-2018
Title: Innovations of Vivek Tyagi in Speech Recognition Technology
Introduction
Vivek Tyagi is a prominent inventor based in New Delhi, India, known for his significant contributions to the field of speech recognition technology. With a total of 12 patents to his name, he has developed innovative methods and systems that enhance the accuracy and efficiency of automatic speech recognition systems.
Latest Patents
Among his latest patents is a method and system for acoustic data selection for training the parameters of an acoustic model. This invention focuses on selecting high-quality acoustic data for training models such as Hidden Markov Models and Gaussian Mixture Models, which are essential in speech analytics. The system employs a series of operations, including forced Viterbi-alignment and phoneme recognition, to create a subset corpus of training data while automatically rejecting poor-quality audio files.
Another notable patent involves modeling a class posterior probability of context-dependent phonemes in a speech recognition system. This invention utilizes a representation network to project an N-dimensional feature vector into multiple intermediate layers. By discretizing the last intermediate layer, the system improves classification accuracy in speech recognition through the determination of posterior probabilities for each (x, b) pair.
Career Highlights
Vivek Tyagi has worked with renowned companies such as IBM and Interactive Intelligence Group, Inc. His experience in these organizations has contributed to his expertise in developing advanced speech recognition technologies.
Collaborations
Throughout his career, Vivek has collaborated with notable professionals, including Aravind Ganapathiraju and Felix Immanuel Wyss. These collaborations have further enriched his work and innovations in the field.
Conclusion
Vivek Tyagi's contributions to speech recognition technology through his patents and collaborations highlight his role as a leading inventor in this domain. His innovative methods continue to shape the future of automatic speech recognition systems.
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