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基于语音识别技术的在线语言翻译交互学习系统的设计与实现 被引量:2
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作者 邓丽君 《自动化与仪器仪表》 2023年第6期199-203,共5页
为实现在线语言翻译交互学习,基于语音识别技术设计并实现了一套在线语言翻译交互学习系统。系统通过采用CNN结合CTC模型与BiLSTM模型构建语音识别声学模型,并采用Transformer模型作为语言模型,实现了语音准确识别,识别字错率低于16%,... 为实现在线语言翻译交互学习,基于语音识别技术设计并实现了一套在线语言翻译交互学习系统。系统通过采用CNN结合CTC模型与BiLSTM模型构建语音识别声学模型,并采用Transformer模型作为语言模型,实现了语音准确识别,识别字错率低于16%,句识别准确率超过95%;然后基于FastSpeech2x声学模型和MelGAN声码器模型,对系统语音合成算法进行设计,实现了高质量的语音合成,MOS评分超过4分。最后,通过对系统语音采集、语音识别和语音合成各个功能模块进行测试,验证了系统性能。测试结果表明,系统各个模块功能完善,可正确执行语音采集、语音识别和语音合成等操作,实现高效率的语音采集、高准确率的语音识别,以及高质量的语音合成,且系统实现语音交互时间不超过5 s,满足语音交互时间需求,且各个功能模块完成相应功能指令的正确率均超过96%,具有良好的用户体验感,可用于实际在线语言翻译学习应用中。 展开更多
关键词 语音识别 在线语言翻译 交互学习 系统设计
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An On-line Assessment System for English-Chinese Translation
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作者 田艳 陆汝占 段建勇 《Journal of Shanghai Jiaotong university(Science)》 EI 2007年第2期180-184,共5页
On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into sc... On-line assessment of English-Chinese translation is a challenging task as it involves natural language processing.YanFa,an on-line assessment system for English-Chinese translation,is a pilot research project into scoring student's translation on-line.Based on the theory of translation equivalence,an algorithm called "conceptual similarity matching" was developed.YanFa can assess students' translation on-line timely,generate test papers automatically,offer standard versions of translation,and the scores of each sentence to students.The evaluation proves that YanFa is practical compared with the scores given by experts. 展开更多
关键词 on-line assessment English-Chinese translation natural language processing
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Query Expansion Using Wikipedia and a Concept Base in Cross-language Information Retrieval
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作者 Pham Huy Anh Yukawa Takashi 《Computer Technology and Application》 2013年第10期522-531,共10页
The present paper describes the use of online free language resources for translating and expanding queries in CLIR (cross-language information retrieval). In a previous study, we proposed method queries that were t... The present paper describes the use of online free language resources for translating and expanding queries in CLIR (cross-language information retrieval). In a previous study, we proposed method queries that were translated by two machine translation systems on the Language Gridem. The queries were then expanded using an online dictionary to translate compound words or word phrases. A concept base was used to compare back translation words with the original query in order to delete mistranslated words. In order to evaluate the proposed method, we constructed a CLIR system and used the science documents of the NTCIR1 dataset. The proposed method achieved high precision. However~ proper nouns (names of people and places) appear infrequently in science documents. In information retrieval, proper nouns present unique problems. Since proper nouns are usually unknown words, they are difficult to find in monolingual dictionaries, not to mention bilingual dictionaries. Furthermore, the initial query of the user is not always the best description of the desired information. In order to solve this problem, and to create a better query representation, query expansion is often proposed as a solution. Wikipedia was used to translate compound words or word phrases. It was also used to expand queries together with a concept base. The NTCIRI and NTCIR 6 datasets were used to evaluate the proposed method. In the proposed method, the CLIR system was implemented with a high rate of precision. The proposed syst had a higher ranking than the NTCIRI and NTCIR6 participation systems. 展开更多
关键词 Cross-language inlbrmation retrieval CLIR language resources concept base language grid Wikipedia.
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