Difference between revisions of "NIPPON TELEGRAPH AND TELEPHONE CORPORATION patent applications published on November 30th, 2023"

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'''Summary of the patent applications from NIPPON TELEGRAPH AND TELEPHONE CORPORATION on November 30th, 2023'''
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NIPPON TELEGRAPH AND TELEPHONE CORPORATION has recently filed several patents related to various technological innovations. These patents cover a range of fields, including wireless communication, user-generated content analysis, battery technology, optical elements, audio signal processing, and voice signal conversion.
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In the field of wireless communication, NTT has developed a learning method that uses machine learning to estimate wireless quality. This method involves training a model with measurement data from multiple terminals and continuously updating the model with new data to improve accuracy. This innovation can enhance the performance and reliability of wireless communication systems.
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Another patent focuses on a device that can determine if user-generated content is generated by a malicious user or a legitimate user. By calculating characteristic amounts of user-generated content and using a learning process, the device creates a model to distinguish between legitimate and malicious content.
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NTT has also developed a relay device with features such as an internal clock, memory, and communication unit for transmitting and receiving signals between a master and a slave. The device uses synchronization signals and a retention time processing unit to ensure accurate signal transmission.
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In the field of battery technology, NTT has filed patents for a metal-air battery with a specific electrolytic solution and a primary battery with unique components. These innovations aim to improve battery performance and enhance energy storage capabilities.
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NTT has also developed an optical element with a transparent layer that guides light to two photoelectric conversion elements. This element is designed to improve image quality and capture more accurate data.
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In the audio signal processing field, NTT has developed techniques for pitch enhancement and high-frequency compensation in decoded sound signals. These innovations aim to improve the quality and naturalness of audio signals.
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Lastly, NTT has filed a patent for a device that learns how to convert voice signals using machine learning models and adjustment parameters. This technology enables the conversion of input voice signals into desired voice signals.
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Notable applications:
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* Learning method for estimating wireless quality using machine learning.
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* Device for determining if user-generated content is generated by a malicious user or a legitimate user.
 +
* Relay device with features for accurate signal transmission.
 +
* Metal-air battery with a specific electrolytic solution.
 +
* Primary battery with unique components.
 +
* Optical element with a transparent layer for improved image quality.
 +
* Techniques for pitch enhancement and high-frequency compensation in audio signals.
 +
* Device for converting voice signals using machine learning models.
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 +
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==Patent applications for nippon telegraph and telephone on November 30th, 2023==
 
==Patent applications for nippon telegraph and telephone on November 30th, 2023==

Revision as of 06:35, 6 December 2023

Summary of the patent applications from NIPPON TELEGRAPH AND TELEPHONE CORPORATION on November 30th, 2023

NIPPON TELEGRAPH AND TELEPHONE CORPORATION has recently filed several patents related to various technological innovations. These patents cover a range of fields, including wireless communication, user-generated content analysis, battery technology, optical elements, audio signal processing, and voice signal conversion.

In the field of wireless communication, NTT has developed a learning method that uses machine learning to estimate wireless quality. This method involves training a model with measurement data from multiple terminals and continuously updating the model with new data to improve accuracy. This innovation can enhance the performance and reliability of wireless communication systems.

Another patent focuses on a device that can determine if user-generated content is generated by a malicious user or a legitimate user. By calculating characteristic amounts of user-generated content and using a learning process, the device creates a model to distinguish between legitimate and malicious content.

NTT has also developed a relay device with features such as an internal clock, memory, and communication unit for transmitting and receiving signals between a master and a slave. The device uses synchronization signals and a retention time processing unit to ensure accurate signal transmission.

In the field of battery technology, NTT has filed patents for a metal-air battery with a specific electrolytic solution and a primary battery with unique components. These innovations aim to improve battery performance and enhance energy storage capabilities.

NTT has also developed an optical element with a transparent layer that guides light to two photoelectric conversion elements. This element is designed to improve image quality and capture more accurate data.

In the audio signal processing field, NTT has developed techniques for pitch enhancement and high-frequency compensation in decoded sound signals. These innovations aim to improve the quality and naturalness of audio signals.

Lastly, NTT has filed a patent for a device that learns how to convert voice signals using machine learning models and adjustment parameters. This technology enables the conversion of input voice signals into desired voice signals.

Notable applications:

  • Learning method for estimating wireless quality using machine learning.
  • Device for determining if user-generated content is generated by a malicious user or a legitimate user.
  • Relay device with features for accurate signal transmission.
  • Metal-air battery with a specific electrolytic solution.
  • Primary battery with unique components.
  • Optical element with a transparent layer for improved image quality.
  • Techniques for pitch enhancement and high-frequency compensation in audio signals.
  • Device for converting voice signals using machine learning models.



Patent applications for nippon telegraph and telephone on November 30th, 2023

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