Minje Kim

Title: Minje Kim: Innovator in Audio Pattern Recognition

Introduction

Minje Kim is a prominent inventor based in Savoy, IL (US), known for her contributions to audio pattern recognition technology. With a total of 6 patents, she has made significant strides in the field of sound data analysis and irregularity detection in music.

Latest Patents

One of her latest patents is titled "Irregular pattern identification using landmark based convolution." This invention describes a method for identifying patterns in sound data by utilizing convolution techniques on frequency and time coordinates. The process involves obtaining a representation of a pattern through data points that include frequency coordinates, time coordinates, and energy values. The identification process determines whether sound data described by irregularly positioned data points corresponds to the identified pattern.

Another notable patent is "Irregularity detection in music." This invention focuses on detecting irregularities in audio streams, particularly in music. The method involves transforming an input signal from the time domain into the frequency domain, generating multiple frames that contain frequency information. By comparing frequency information across these frames, the system can identify irregular events in the audio signal, allowing for synchronization with multimedia events.

Career Highlights

Minje Kim is currently employed at Adobe Systems Inc., where she continues to innovate and develop new technologies in audio processing. Her work has garnered attention for its potential applications in various multimedia and entertainment industries.

Collaborations

Minje has collaborated with notable colleagues, including Paris Smaragdis and Gautham J Mysore, contributing to advancements in audio technology through teamwork and shared expertise.

Conclusion

Minje Kim's innovative work in audio pattern recognition and irregularity detection showcases her significant contributions to the field. Her patents reflect a deep understanding of sound data analysis, paving the way for future advancements in audio technology.