Princeton Junction, NJ, United States of America

Michelle Paulette Martin


Average Co-Inventor Count = 7.0

ph-index = 1

Forward Citations = 17(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Michelle Paulette Martin: Innovator in Interview Assessment Technology

Introduction

Michelle Paulette Martin is a notable inventor based in Princeton Junction, NJ (US). She has made significant contributions to the field of interview assessment technology. With one patent to her name, her work focuses on enhancing the evaluation of structured interview responses through innovative methods.

Latest Patents

Michelle's patent, titled "Systems and methods for assessing structured interview responses," utilizes supervised machine learning to create a model for scoring interview responses. The system is designed to access a training response, which may include an audiovisual recording of a person answering an interview question. This training response is assigned a human-determined score. The system extracts delivery and content features from the audiovisual recording and uses these features along with the human-determined score to train a response scoring model. This model is capable of automatically assigning scores to audiovisual recordings of interview responses, providing interviewers with valuable insights to assess candidates effectively.

Career Highlights

Michelle is currently employed at Educational Testing Service, where she applies her expertise in developing assessment technologies. Her innovative approach to interview scoring has the potential to transform how candidates are evaluated in various sectors.

Collaborations

Some of Michelle's coworkers include Patrick Charles Kyllonen and Lei Chen, who contribute to the collaborative environment at Educational Testing Service.

Conclusion

Michelle Paulette Martin's work in interview assessment technology exemplifies the impact of innovation in improving candidate evaluation processes. Her patent demonstrates a forward-thinking approach that leverages machine learning to enhance the accuracy and efficiency of interviews.

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