Tel Aviv, Israel

Eli Asor

USPTO Granted Patents = 3 

Average Co-Inventor Count = 6.3

ph-index = 2

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2020-2021

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3 patents (USPTO):Explore Patents

Title: Eli Asor: Innovator in Automatic Speech Recognition

Introduction

Eli Asor is a notable inventor based in Tel Aviv, Israel. He has made significant contributions to the field of automatic speech recognition (ASR) through his innovative patents. With a total of 3 patents, Asor's work focuses on enhancing the accuracy and efficiency of transcription systems.

Latest Patents

One of Eli Asor's latest patents is titled "Human resolution of repeated phrases in a hybrid transcription system." This invention addresses the common issue of repeated phrases being incorrectly transcribed by ASR systems during audio recordings, such as legal depositions. The system assists transcribers by clustering segments of audio recordings into similar utterances, allowing for more accurate transcriptions.

Another significant patent is "Human-based accent detection to assist rapid transcription with automatic speech recognition." This invention aims to improve ASR systems by identifying the accent of speakers in audio recordings. By providing transcribers with accent indications, the system enhances the accuracy of transcriptions for various audio segments.

Career Highlights

Eli Asor is currently employed at Verbit Software Ltd., where he continues to develop innovative solutions in the field of speech recognition. His work at Verbit has positioned him as a key player in advancing transcription technology.

Collaborations

Asor collaborates with talented individuals such as Eric Ariel Shellef and Yaakov Kobi Ben Tsvi. Their combined expertise contributes to the development of cutting-edge technologies in the ASR domain.

Conclusion

Eli Asor's contributions to automatic speech recognition through his patents demonstrate his commitment to innovation in transcription technology. His work not only enhances the accuracy of transcriptions but also improves the overall efficiency of audio processing systems.

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