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For the Inventor, By the Inventor

New York, NY, United States of America

Frederick Victor Weber

USPTO Granted Patents = 13

Average Co-Inventor Count = 2.2

ph-index = 8

Forward Citations = 818(Granted Patents)


Company Filing History:

goldMedal13 out of 22,475 
 
Amazon Technologies, Inc.
 patents

Years Active: 2015-2025

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13 patents (USPTO):
1. 12488798 - Continuous learning for machine learning models (2025-12-02),
2. 11900948 - Automatic speaker identification using speech recognition features (2024-02-13),
3. 11222639 - Automatic speaker identification using speech recognition features (2022-01-11),
4. 10665245 - Automatic speaker identification using speech recognition features (2020-05-26),
5. 10332525 - Automatic speaker identification using speech recognition features (2019-06-25),
6. 10149077 - Audio themes (2018-12-04),
7. 9558749 - Automatic speaker identification using speech recognition features (2017-01-31),
8. 9495955 - Acoustic model training (2016-11-15),
9. 9401140 - Unsupervised acoustic model training (2016-07-26),
10. 9292487 - Discriminative language model pruning (2016-03-22),
11. 9275637 - Wake word evaluation (2016-03-01),
12. 9224386 - Discriminative language model training using a confusion matrix (2015-12-29),
13. 9153231 - Adaptive neural network speech recognition models (2015-10-06),

Title: The Innovations of Frederick Victor Weber

Introduction

Frederick Victor Weber is a notable inventor based in New York, NY, with a remarkable portfolio of 12 patents. His work primarily focuses on advancements in speech recognition technology, contributing significantly to the field.

Latest Patents

One of Weber's latest patents is centered around automatic speaker identification using speech recognition features. This innovation discloses methods for automatically identifying a speaker by processing artifacts of automatic speech recognition (ASR) and other determined information against individual user profiles or models. The system determines scores that reflect the likelihood of individual users making an utterance. These scores are based on components of Gaussian mixture models (GMMs) that best score frames of audio data from an utterance. The user with the highest likelihood score for a specific utterance is identified as the speaker. This information can then be utilized by components of a spoken language processing system and separate applications.

Career Highlights

Weber is currently employed at Amazon Technologies, Inc., where he continues to innovate and develop new technologies. His contributions have been instrumental in enhancing the capabilities of speech recognition systems.

Collaborations

Throughout his career, Weber has collaborated with talented individuals such as Hugh Evan Secker-Walker and Baiyang Liu. These collaborations have fostered a creative environment that has led to significant advancements in their respective fields.

Conclusion

Frederick Victor Weber's contributions to speech recognition technology exemplify the impact of innovation in modern communication systems. His work continues to influence the development of automated systems that enhance user interaction and experience.

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