BRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives

Rodrigues, Rafael Guimarães; Rodrigues, Kaio Tavares; Gomes, Rodrigo Reis; Ferrari, Lílian; Ogasawara, Eduardo; Guedes, Gustavo Paiva

doi:10.1109/tla.2020.9099768

IEEE Latin Am. Trans.

2020

DOI: 10.1109/tla.2020.9099768

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BRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives

Rafael Guimarães Rodrigues

Kaio Tavares Rodrigues

Rodrigo Reis Gomes

et al.

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Cited by 2 publications

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“…

To determine if translation is necessary, the fuzzy logic approach is often used 10 . make sure that your criteria are tailored to produce the most reliable data for fuzzy match.

…”

mentioning

confidence: 99%

Analyzing the impact of deep learning algorithms and fuzzy logic approach for remote English translation

Han

2024

Sci Rep

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A remote English translation is used for assisting with on-demand support for adaptable sentence conversion and language understanding. The problem with on-demand translations is the precision verification of the words used. This article addresses the precision problem by assimilating deep learning and fuzzy decision algorithm for remote translation support. The method named Fusion-dependent Precision Translation Approach (FPTA) conducts a series of recurrent validations on word usage and sentence completion for the given inputs. First, the completed sentences are verified using the understandability and meaning intended using deep learning in two recurrent layers. The first layer is responsible for identifying word placement and understandability and the second is responsible for meaning verification. The recurrent training is tuned using a fuzzy decision algorithm by selecting the maximum best-afford solution. The constraint’s understandability and meaning are augmented for tuning the outputs by preventing errors consequently. In precise, the error sequences are identified from the first layer for fuzzification across various inputs. This process improves the word adaptability from different languages reducing errors (12.49%) and improves the understandability (11.57%) for various translated sentences.

show abstract

“…

To determine if translation is necessary, the fuzzy logic approach is often used 10 . make sure that your criteria are tailored to produce the most reliable data for fuzzy match.

…”

mentioning

confidence: 99%

Analyzing the impact of deep learning algorithms and fuzzy logic approach for remote English translation

Han

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

WITHDRAWN: English corpus translation system based on FPGA and machine learning

Zhao

2020

Microprocessors and Microsystems

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BRAPT: A New Metric for Translation Evaluation Based on Psycholinguistic Perspectives

Cited by 2 publications

References 22 publications

Analyzing the impact of deep learning algorithms and fuzzy logic approach for remote English translation

Analyzing the impact of deep learning algorithms and fuzzy logic approach for remote English translation

WITHDRAWN: English corpus translation system based on FPGA and machine learning

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