一种用于文本方言识别的转换器微调策略。

IF 4.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Mohammad Ali Humayun, Hayati Yassin, Junaid Shuja, Abdullah Alourani, Pg Emeroylariffion Abas
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引用次数: 2

摘要

在线医疗咨询可以显著提高初级卫生保健的效率。最近,许多在线医疗问答服务已经开发出来,根据患者的问题将患者与相关的医疗顾问联系起来。考虑到他们问题中的语言多样性,患者的社会背景识别可以通过选择具有相似社会背景的医疗咨询师来改善转诊系统,从而进行有效的沟通。本文提出了一种新的微调策略,用于预先训练的变形器识别文本作者的社会来源。当与已有的适配器模型相融合时,本文提出的方法在细致入微的阿拉伯语方言识别(NADI)数据集上的阿拉伯语方言识别任务的总体准确率达到53.96%。总体精度比之前相同数据集的最佳精度高0.54%,这为预训练的变压器模型建立了自定义微调策略的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A transformer fine-tuning strategy for text dialect identification.

A transformer fine-tuning strategy for text dialect identification.

A transformer fine-tuning strategy for text dialect identification.

A transformer fine-tuning strategy for text dialect identification.

Online medical consultation can significantly improve the efficiency of primary health care. Recently, many online medical question-answer services have been developed that connect the patients with relevant medical consultants based on their questions. Considering the linguistic variety in their question, social background identification of patients can improve the referral system by selecting a medical consultant with a similar social origin for efficient communication. This paper has proposed a novel fine-tuning strategy for the pre-trained transformers to identify the social origin of text authors. When fused with the existing adapter model, the proposed methods achieve an overall accuracy of 53.96% for the Arabic dialect identification task on the Nuanced Arabic Dialect Identification (NADI) dataset. The overall accuracy is 0.54% higher than the previous best for the same dataset, which establishes the utility of custom fine-tuning strategies for pre-trained transformer models.

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来源期刊
Neural Computing & Applications
Neural Computing & Applications 工程技术-计算机:人工智能
CiteScore
11.40
自引率
8.30%
发文量
1280
审稿时长
6.9 months
期刊介绍: Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems. All items relevant to building practical systems are within its scope, including but not limited to: -adaptive computing- algorithms- applicable neural networks theory- applied statistics- architectures- artificial intelligence- benchmarks- case histories of innovative applications- fuzzy logic- genetic algorithms- hardware implementations- hybrid intelligent systems- intelligent agents- intelligent control systems- intelligent diagnostics- intelligent forecasting- machine learning- neural networks- neuro-fuzzy systems- pattern recognition- performance measures- self-learning systems- software simulations- supervised and unsupervised learning methods- system engineering and integration. Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
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