Maple Valley, WA, United States of America

Hansel Guzman-Soto

This inventor holds 1 USPTO granted patent. Top assignee: Snap Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Hansel Guzman-Soto. Retrieved from https://idiyas.com/inventor/hansel-guzman-soto

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Hansel Guzman-Soto: Inventor of Wearable Speech-Detection Technology.

Introduction

Hansel Guzman-Soto is an inventor based in Maple Valley, Washington. His work includes a patent for technology designed to help wearable devices distinguish a wearer’s speech from nearby voices.

Latest Patents

Guzman-Soto is named on 1 patent: “Bystander Speech Command Rejection for Wearable Devices.” The patent describes a head-wearable apparatus with multiple spatially separated microphones, processors, and computer-readable storage. The microphones generate audio signals that are processed using a trained machine-learning model to produce data indicating the likelihood that the wearer is speaking. This approach is intended to help reject speech commands from bystanders.

Career Highlights

Guzman-Soto works at Snap Inc. His patented work focuses on applying machine learning and multiple microphones to speech detection in wearable devices.

Collaborations

His listed coworkers include Daniel Harris and Connor Cabrera. The patent information provided identifies Guzman-Soto as an inventor but does not specify whether these coworkers collaborated with him on the patent.

Conclusion

Hansel Guzman-Soto’s patent addresses a practical challenge in wearable technology by using spatially separated microphones and machine learning to identify when the wearer is speaking.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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