Tokyo, Japan

Takaaki Fukutomi

USPTO Granted Patents = 6 

Average Co-Inventor Count = 2.9

ph-index = 1


Location History:

  • Yokohama, JP (2023)
  • Tokyo, JP (2022 - 2024)

Company Filing History:


Years Active: 2022-2024

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6 patents (USPTO):

Title: Takaaki Fukutomi: Innovator in Acoustic Model Learning

Introduction

Takaaki Fukutomi is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of acoustic model learning, holding a total of 6 patents. His work focuses on enhancing sound recognition technology, which has applications in various industries.

Latest Patents

Fukutomi's latest patents include an acoustic model learning apparatus, an acoustic model learning method, and a program. These innovations provide a technology for learning an acoustic model with a certain degree of accuracy in sound recognition within a short calculation period. The acoustic model learning device features a loss calculation unit that computes the loss of sound data, a curriculum corpus generation unit that creates a curriculum corpus from subsets of learning corpuses, and an acoustic model update unit that refines the acoustic model based on the curriculum corpus. Additionally, a learning data acquisition apparatus is designed to acquire learning data by superimposing noise data on clean voice data at an appropriate signal-to-noise ratio.

Career Highlights

Fukutomi is currently employed at Nippon Telegraph and Telephone Corporation, where he continues to innovate in the field of acoustic technology. His work has been instrumental in advancing sound recognition systems, making them more efficient and accurate.

Collaborations

Some of his notable coworkers include Takashi Nakamura and Kiyoaki Matsui. Their collaborative efforts contribute to the ongoing research and development in acoustic model learning.

Conclusion

Takaaki Fukutomi's contributions to acoustic model learning demonstrate his commitment to innovation in sound recognition technology. His patents reflect a deep understanding of the complexities involved in this field, paving the way for future advancements.

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