Boe technology group co., ltd. (20240185840). METHOD OF TRAINING NATURAL LANGUAGE PROCESSING MODEL METHOD OF NATURAL LANGUAGE PROCESSING, AND ELECTRONIC DEVICE simplified abstract

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METHOD OF TRAINING NATURAL LANGUAGE PROCESSING MODEL METHOD OF NATURAL LANGUAGE PROCESSING, AND ELECTRONIC DEVICE

Organization Name

boe technology group co., ltd.

Inventor(s)

Bingqian Wang of BEIJING (CN)

METHOD OF TRAINING NATURAL LANGUAGE PROCESSING MODEL METHOD OF NATURAL LANGUAGE PROCESSING, AND ELECTRONIC DEVICE - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240185840 titled 'METHOD OF TRAINING NATURAL LANGUAGE PROCESSING MODEL METHOD OF NATURAL LANGUAGE PROCESSING, AND ELECTRONIC DEVICE

Simplified Explanation

The present disclosure describes a method for training a natural language processing model, a method of natural language processing, and an electronic device. The method involves acquiring corpus data for training, processing the corpus data using a natural language processing model to obtain output information, and training the model based on the output information.

  • Acquiring corpus data for training
  • Processing the corpus data using a natural language processing model
  • Training the model based on the output information

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      1. Potential Applications of this Technology

- Improving accuracy and efficiency of natural language processing tasks - Enhancing text transformation capabilities in electronic devices

      1. Problems Solved by this Technology

- Correcting pinyin data in corpus data - Performing text transformation on corrected pinyin data

      1. Benefits of this Technology

- Enhanced performance of natural language processing models - Improved text processing capabilities in electronic devices

      1. Potential Commercial Applications of this Technology
        1. Optimizing Natural Language Processing Models for Electronic Devices

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      1. Possible Prior Art

There may be prior art related to training natural language processing models using multiple models for different tasks, such as correcting pinyin data and performing text transformation. This could include research papers, patents, or existing products in the field of natural language processing.

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    1. Unanswered Questions
      1. How does this method compare to existing techniques for training natural language processing models?

This article does not provide a direct comparison to other methods or techniques commonly used in the field of natural language processing. Further research or experimentation may be needed to evaluate the effectiveness and efficiency of this approach compared to existing practices.

      1. What are the specific limitations or challenges associated with implementing this method in real-world applications?

The article does not address potential obstacles or constraints that may arise when applying this method to practical scenarios. Understanding the limitations and challenges of integrating this technology into existing systems is crucial for successful implementation.


Original Abstract Submitted

the present disclosure relates to a method of training a natural language processing model, a method of natural language processing, and an electronic device. the method of training a natural language processing model includes: acquiring corpus data for training; processing the corpus data by using a natural language processing model to obtain output information, wherein the natural language processing model includes a first model for correcting pinyin data of the corpus data and a second model for performing text transformation on the corrected pinyin data of the corpus data; and training the natural language processing model according to the output information of the natural language processing model to obtain the trained natural language processing model.

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