Hyundai motor company (20240202462). Apparatus And Method For Data Augmentation simplified abstract
Contents
Apparatus And Method For Data Augmentation
Organization Name
Inventor(s)
Yekyung Kim of Seongnam-Si (KR)
Seohyeong Jeong of Suwon-Si (KR)
Kyunghyun Cho of New York NY (US)
Apparatus And Method For Data Augmentation - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202462 titled 'Apparatus And Method For Data Augmentation
The patent application describes an apparatus for data augmentation that involves encoding input sentences, adjusting their length, mixing them at a predetermined ratio, and generating a new sentence based on the interpolated hidden vector.
- Encoder encodes input sentences to output encoded samples.
- Generation part adjusts length of encoded samples to match target length.
- Generation part mixes adjusted length samples to generate interpolated hidden vector.
- Decoder reconstructs original sentence from interpolated hidden vector.
Potential Applications: - Natural language processing tasks - Text generation for chatbots or virtual assistants - Data augmentation for machine learning models
Problems Solved: - Enhances the diversity and quality of training data - Improves the performance of natural language processing models
Benefits: - Increased accuracy and robustness of language models - Enhanced capabilities for text generation tasks
Commercial Applications: Title: Advanced Data Augmentation Technology for Natural Language Processing This technology can be utilized in various industries such as: - E-commerce for personalized product recommendations - Healthcare for analyzing medical records - Finance for fraud detection and risk assessment
Questions about the technology: 1. How does this data augmentation technique improve the performance of natural language processing models? 2. What are the potential limitations of using this apparatus for data augmentation in real-world applications?
Original Abstract Submitted
an apparatus for data augmentation includes an encoder configured to encode a plurality of input sentences and output encoded samples based on the plurality of encoded input sentences; a generation part configured to adjust a length of each of the encoded samples to match a target length, and mix the encoded samples having the adjusted length at a predetermined mixing ratio to generate an interpolated hidden vector of a newly generated sentence; and a decoder configured to reconstruct an original sentence corresponding to the interpolated hidden vector.
