Twi机器翻译

IF 3.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Big Data and Cognitive Computing Pub Date : 2023-06-08 DOI:10.3390/bdcc7020114
Frederick Gyasi, Tim Schlippe
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引用次数: 1

摘要

在使用非洲语Twi的地区,法语是一种具有重要战略意义和经济意义的语言。然而,在加纳讲Twi的人中,只有极少数人说法语。Twi-French平行语料库和相应的机器翻译应用程序的开发将提供各种优势,包括刺激贸易和创造就业机会,支持法语国家的加纳侨民,帮助在加纳寻求医疗服务的法语游客和移民,以及促进许多下游自然语言处理任务。由于Twi和法语之间几乎没有任何机器翻译系统或平行语料库覆盖现代通用词汇,我们的目标是用法语扩展现代Twi-英语语料库,并开发Twi和法国之间的机器翻译系统:因此,在本文中,我们展示了10708个平行句子的Twi-法语语料库。此外,我们还用这个语料库描述了我们的机器翻译实验。我们研究了使用英语作为中枢语言的直接机器翻译和级联系统。我们最好的Twi-Franch系统是一个最先进的基于变压器的机器翻译系统,其BLEU得分为0.76。我们最好的法语-Twi系统是一个以英语为核心语言的级联系统,其BLEU得分为0.81。这两个系统都与我们的语料库进行了微调,我们的French–Twi系统在我们的测试集上甚至略优于Google Translate 7%。
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Twi Machine Translation
French is a strategically and economically important language in the regions where the African language Twi is spoken. However, only a very small proportion of Twi speakers in Ghana speak French. The development of a Twi–French parallel corpus and corresponding machine translation applications would provide various advantages, including stimulating trade and job creation, supporting the Ghanaian diaspora in French-speaking nations, assisting French-speaking tourists and immigrants seeking medical care in Ghana, and facilitating numerous downstream natural language processing tasks. Since there are hardly any machine translation systems or parallel corpora between Twi and French that cover a modern and versatile vocabulary, our goal was to extend a modern Twi–English corpus with French and develop machine translation systems between Twi and French: Consequently, in this paper, we present our Twi–French corpus of 10,708 parallel sentences. Furthermore, we describe our machine translation experiments with this corpus. We investigated direct machine translation and cascading systems that use English as a pivot language. Our best Twi–French system is a direct state-of-the-art transformer-based machine translation system that achieves a BLEU score of 0.76. Our best French–Twi system, which is a cascading system that uses English as a pivot language, results in a BLEU score of 0.81. Both systems are fine tuned with our corpus, and our French–Twi system even slightly outperforms Google Translate on our test set by 7% relative.
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来源期刊
Big Data and Cognitive Computing
Big Data and Cognitive Computing Business, Management and Accounting-Management Information Systems
CiteScore
7.10
自引率
8.10%
发文量
128
审稿时长
11 weeks
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