Company Filing History:
Years Active: 2020-2024
Title: Innovations of Prem Seetharaman in Audio Identification
Introduction
Prem Seetharaman is an accomplished inventor based in Chicago, IL (US). He has made significant contributions to the field of audio identification, holding a total of six patents. His work focuses on advanced systems and methods for identifying audio content, particularly in the context of cover songs.
Latest Patents
One of his latest patents is titled "Audio identification based on data structure." This invention discloses systems and methods that utilize a constant Q transform on query audio to identify it as a cover rendition of reference audio. The apparatus includes memory and processors that execute instructions to binarize transformed audio slices and perform a two-dimensional Fourier transform. This process generates a query data structure that can be compared to a reference data structure associated with the original audio.
Another notable patent is "Automated cover song identification." This invention outlines a method for identifying cover songs through a similar process. The apparatus executes a constant Q transform on audio data, binarizes the transformed slices, and performs a two-dimensional Fourier transform. The resulting reference data structure is stored in a database, allowing for the identification of query audio data as a cover rendition based on a comparison with the reference data structure.
Career Highlights
Prem Seetharaman is currently employed at Gracenote, Inc., where he continues to innovate in the field of audio technology. His work has been instrumental in enhancing the accuracy and efficiency of audio identification systems.
Collaborations
Throughout his career, Prem has collaborated with notable colleagues, including Zafar Rafii and Markus Kurt Cremer. These collaborations have contributed to the development of cutting-edge technologies in audio identification.
Conclusion
Prem Seetharaman's contributions to audio identification through his innovative patents have significantly advanced the field. His work at Gracenote, Inc. exemplifies the impact of technology on music recognition and identification.