Hyderabad Telangana, India

Ram Sundaram


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:

goldMedal1 out of 832,843 
Other
 patents

Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Ram Sundaram - Innovator in Neural Network Based Speaker Classification

Introduction

Ram Sundaram is a notable inventor based in Hyderabad, Telangana, India. He has made significant contributions to the field of speaker recognition technology. His innovative approach focuses on utilizing neural networks for classifying speakers based on their unique audio characteristics.

Latest Patents

Ram Sundaram holds a patent for a "System and method for neural network based speaker classification." This patent describes a method for classifying speakers that involves several key steps. The process begins with receiving input audio that includes speech from a speaker. The speaker recognition system then extracts a plurality of speech frames containing voiced speech from the input audio. Following this, the system computes a variety of features for each of the speech frames. It also calculates recognition scores for these features and ultimately derives a speaker classification result based on the recognition scores. The system then outputs the speaker classification result, showcasing the effectiveness of his invention.

Career Highlights

Throughout his career, Ram Sundaram has demonstrated a strong commitment to advancing technology in the field of audio processing. His work has not only contributed to academic knowledge but has also paved the way for practical applications in various industries.

Collaborations

Ram has collaborated with talented individuals such as Zhenhao Ge and Ananth Nagaraja Iyer. These partnerships have enriched his research and development efforts, leading to innovative solutions in speaker classification.

Conclusion

In summary, Ram Sundaram is a pioneering inventor whose work in neural network based speaker classification has the potential to transform the way we understand and utilize audio recognition technology. His contributions are significant and continue to influence the field.

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