PACLIC-27
Vietnamese to Chinese Machine Translation via Chinese Character as Pivot∗
Hai Zhao1,2† Tianjiao Yin3 Jingyi Zhang1,2 (1) MOE-Microsoft Key Laboratory of Intelligent Computing and Intelligent System (2) Department of Computer Science and Engineering, Shanghai Jiao Tong University #800 Dongchuan Road, Shanghai, China, 200240 (3) Facebook, Inc. 1601 Willow Rd. Menlo Park, CA 94025 USA [email protected], [email protected] [email protected]
Abstract
Using Chinese characters as an intermedi- ate equivalent unit, we decompose machine translation into two stages, semantic transla- tion and grammar translation. This strategy is tentatively applied to machine translation between Vietnamese and Chinese. During the semantic translation, Vietnamese sylla- bles are one-by-one converted into the cor- responding Chinese characters. During the grammar translation, the sequences of Chi- Figure 1: The phrase Chinese character culture sphere nese characters in Vietnamese grammar or- written in Chinese characters from different regions. der are modified and rearranged to form grammatical Chinese sentence. Compared to the existing single alignment model, the t SMT (Chu et al., 2012), though their approach- division of two-stage processing is more tar- es still follow the standard processing pipeline of geted for research and evaluation of machine SMT. For those resource-poor languages, a pivot translation. The proposed method is evalu- ated using the standard BLEU score and a language will be used as an expedience (Utiyama new manual evaluation metric, understand- and Isahara, 2007; Wu and Wang, 2009). ing rate. Only based on a small number In this work, we focus on machine translation of dictionaries, the proposed method gives (MT) for language pairs with few parallel corpora competitive and even better results com- but rich linguistic connections. A case study on pared to existing systems. Vietnamese and Chinese will be done. To exploit the shared linguistic characteristics between the 1 Introduction language pair, the common written form, Chinese character, is adopted as a translation bridge. Be- The statistical machine translation (SMT) has been ing the oldest continuously used writing system in well developed from a basis of data-drive idea s- the world, Chinese characters are logograms that ince the work of (Brown et al., 1993). How- are still used to write Chinese (汉字/漢字 in Chi- ever, a large amount of parallel corpora are al- nese, hànzì in Chinese pinyin) and Japanese (kan- ways necessary to build a standard SMT system ji). Such characters were used but are currently for a specific language pair, regardless of the pos- less frequently used in Korean (hanja), and were sible useful linkages between these two languages. also used in Vietnamese (chữ Hán). All the coun- There is existing work that considered using help- tries that were historically under Chinese language ful linguistic heuristics to enhance the curren- and culture are unofficially referred to Chinese This∗ work was partially supported by the National Natu- character cultural sphere or Sinosphere. These t- ral Science Foundation of China (Grant No.60903119, Grant wo terms are often used interchangeably but have No.61170114, and Grant No.61272248), and the National Basic Research Program of China (Grant No.2009CB320901 different denotations (Matisoff, 1990). A Chinese and Grant No.2013CB329401). character writing example of different regions is in corresponding† author Figure 1.
250 Copyright 2013 by Hai Zhao, Tianjiao Yin, and Jingyi Zhang 27th Pacific Asia Conference on Language, Information, and Computation pages 250－259 PACLIC-27
as corpus building, primary processing tasks, etc. A few studies have been done on Vietnamese related MT, though nearly all MT studies on Viet- namese focus on English as source or target lan- guage. As Vietnamese is an under-resourced lan- guage, most Vietnamese MT systems adopted rule based methods (Le et al., 2006; Le and Phan, 2009; Le and Phan, 2010). (Pham et al., 2009) used word-by-word trans- lation incorporated with predefined templates to Figure 2: Different scripts for Chinese characters. perform English-Vietnamese translation on weath- er bulletin texts. The similar strategy was also used in (Hoang et al., 2012) for Vietnamese to Ka- There are tens of thousands of Chinese charac- tu language translation on the same domain. ters, though most of them are minor graphic vari- Until very recently, the statistical approach was ants only existing in historical texts as Figure 2. applied to Vietnamese related MT task. (N- Mastering modern Chinese usually requires know- guyen and Shimazu, 2006; Nguyen et al., 2008) ing 2,000-4,000 characters. Though most words used self-defined morphological transformation in modern Chinese consist of two or more char- and syntactic transformation to beforehand solve acters, each Chinese character may correspond to reordering problem for Vietnamese-English trans- a spoken syllable with a distinct meaning. Be- lation. (Thi and Dinh, 2008) introduced a word ing meaning-oriented representation units, Chi- re-ordering approach that makes use of the syn- nese characters are naturally suitable to act as a tactic rules extracted from parse tree for English- bridge of semantic representation for translation Vietnamese MT. (Bui et al., 2010) proposed lan- task. This process will be especially promising as guage dependent features to enhance Vietnamese- we are working on a language like Vietnamese. English SMT. (Nguyen et al., 2012) integrated Vietnamese (tiếng Việt) is spoken by about more knowledge about the topic of the text, part- eighty million people. Much of Vietnamese vo- of-speech and morphology to resolve semantic cabulary has been borrowed from Chinese, and ambiguity of words during translation. Based on it formerly used a modified Chinese writing sys- empirical observation, (Nguyen and Dinh, 2012) tem, Chữ Nôm, and given vernacular pronuncia- proposed a group of heuristic patterns to discover tion. The Vietnamese alphabet (Quốc Ngữ) in use the alignment errors. (Bui et al., 2012) proposed a today is a Latin alphabet with additional diacritics group of rules to split long Vietnamese sentences for tones, and certain letters. based on linguistic information to enhance Viet- In this paper, a novel two-stage approach is pro- namese to English MT. posed for Vietnamese to Chinese MT by adopting Few studies have been done for MT task be- Chinese characters as the pivot. Vietnamese syl- tween Vietnamese and Chinese as to our best lables will first be converted into Chinese charac- knowledge. For such a low resource language pair, ters according to the meaning equivalence. Then rule based MT systems are too hard to build, and Chinese character sequences in Vietnamese gram- statistical MT systems require too large parallel mar order will be modified and reordered into corpus that is also difficultly acquired. Though grammatical Chinese. The proposed approach on- Chinese characters have been considered a useful ly requires a small number of linguistic resources, intermediate form for MT, few studies made a ful- such as bilingual dictionaries and monolingual l use of them. Instead, most existing approaches language model, to work effeciently. focus on the role of Chinese word during transla- 2 Related Work tion (Chang et al., 2008; Xu et al., 2008; Dyer et al., 2008; Ma and Way, 2009; Paul et al., 2010; Only recently have researchers begun to be in- Nguyen et al., 2010). (Chu et al., 2012) exploit- volved in the domain of Vietnamese language pro- ed shared Chinese characters between Chinese and cessing. Most work on Vietnamese language pro- Japanese to improve the concerned translation per- cessing has to still focus on very basic issues such formance. The most recent work (Xi et al., 2012)
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Vietnamese Chinese rately used as a meaningful unit. Like Chinese, Character Chữ Nôm Chinese characters most Vietnamese words are bi-syllable. Chinese script (official now) is written without blanks between words and Viet- Romanized Quốc Ngữ pinyin namese is written with blanks between two sylla- script (official now) bles instead of words. Thus word segmentation becomes a primary processing for both languages. Table 1: Chinese vs. Vietnamese: writing systems Vietnamese is a prop-drop (pronoun-dropping) language, which means that certain classes of pro- proposed using Chinese character as aligning u- nouns in Vietnamese may be omitted when they nit. However, both of the above works are different are in some sense pragmatically inferable. Chi- from ours, in which Chinese characters are used as nese also exhibits frequent pro-drop features. a pivot for translation task for the first time. Both Chinese and Vietnamese allow verb seri- alization. Contrary to subordination in English 3 Chinese Elements inside Vietnamese where one clause is embedded into another, the se- 3.1 The Same and The Difference rial verb construction is a syntactic phenomenon that two verbs are put together in a sequence in Most linguists agree that Chinese and Vietnamese which no verb is subordinated to the other. belong to two quite different language families. Different from Chinese on word order, Viet- All varieties of modern Chinese are usually cate- namese is head-initial, i.e., displaying modified- gorized as part of the Sino-Tibetan language fam- modifier ordering, but number and noun classifier ily. However, opinions are divided on the lan- being before the modified noun. Thus, for exam- guage family that Vietnamese should belong to, ple, the Vietnamese language in Vietnamese gram- though the most acceptable view is that it is part mar order should not be Vietnamese language of the Mon–Khmer branch of the Austroasiatic (Việt Nam tiếng) but language Vietnamese (tiếng language family according to the observation that Việt Nam ). Vietnamese and Khmer share a lot of cognates and basic grammar (Benedict, 1944; Nguyen, 2008). 3.2 Sino-Vietnamese A writing system comparison between Chinese and Vietnamese is shown in Table 1. An obvious As a result of close ties with China for more than distinction between Vietnamese and Chinese writ- 2,000 years, quite a few of the Vietnamese lex- ing is on the role of the Romanized scripts. The ical elements have Chinese roots. The elements Quốc Ngữ is official writing system of Vietnamese in the Vietnamese derived from Chinese is called today, while pinyin is only an assistant language Sino-Vietnamese (Hán Việt; 漢 越), which ac- learning tool for Chinese today. counts for about 30-60% of the Vietnamese vo- Both Chinese and Vietnamese, like many lan- cabulary (LUO, 2011). This vocabulary was orig- guages in East Asia, are analytic (isolating) lan- inally written with Chinese characters, but like all guages1. Neither of them uses morphological written Vietnamese, is now written with the Quốc marking of case, gender, number or tense. Both Ngữ, the Latin-based Vietnamese alphabet. Sino- languages use word order and function words to Vietnamese words have a status similar to that of convey grammar relationships. As word order or Latin-based words in English: they are used more function words are changed, the meaning will be in formal occasion than in everyday life. Most changed accordingly. Moreover, their syntax both monosyllabic Sina-Vietnamese are used for word- conforms to subject-verb-object word order and building morphemes, though a few of them may possesses noun classifier systems. be directly adopted as words as well. As each Chinese character in Chinese represents A lot of Sino-Vietnamese words, such as those a meaningful unit, a major feature of Vietnamese in Table 2, have the exactly same meaning as mod- word-building is that each syllable may be sepa- ern Chinese. Some Sino-Vietnamese words (Ta- ble 3) are written in the same Chinese character- 1 A few linguists strictly define that an isolating language s but represent different meaning from their Chi- as a type of language with a low morpheme-per-word ratio nese counterparts. Some Sino-Vietnamese words is a closely related concept of the analytic language, but stil- l different from the latter. In this paper, we do not strictly (Table 4)are entirely invented by the Vietnamese, distinguish these two concepts. which can be directly written in Chines characters
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Vietnamese Chinese Chinese meaning and other languages such as Japanese and Kore- words characters pinyin an usually borrow Chinese Characters semantical- lịch sử 歷史 lì shˇı history ly rather than phonetically, and the Chinese char- 定義 định nghĩa dìng yì definition acter scripts also continuously evolved in the past phong phú 豐富 feng¯ fù fruitful thời sự 時事 shí shì current events 3,000 years as shown in Figure 2. Meanwhile, the meaning that Chinese character Table 2: A list of Sina-Vietnamese words was initially invented to express seldom changes over time. Chinese characters used in the similar Vietnamese Vietnamese Chinese Chinese way for different languages also share the same or in Latin in chữ Hán word meaning similar meaning, which is especially obvious for linh mục 靈牧牧牧 牧牧牧师 clergyman Chinese characters borrowed by Japanese (kanji). lí thuyết 理理理說 理理理论 theory For example, although the character ‘ 山’ in Fig- bệnh cảm 病感感感 感感感冒 flu ure 2, has more than 8 different writing scripts, khẩu trang 口口口裝 口口口罩 mask and may be pronounced as shan in Mandarin Chi- yama san Table 4: A list of Sina-Vietnamese words with similar nese, either or in modern Japanese, it is writing and same meaning always referred to the meaning ‘mountain’ in both languages. In addition, Chinese character writing system but not used in Chinese or no longer used in mod- is usually more accurate than alphabetic writing ern Chinese. Interestingly, though not exactly the systems on expressive ability. In fact, Chinese, same in writing, there is always one character that Vietnamese and Korean are the victims of a large is shared by both languages for words in Table 4. amount of homophones in their vocabulary. How- Writing Sino-Vietnamese words with Quốc Ngữ ever, modern Korean and Vietnamese that have may cause some confusions due to the large adopted alphabetic writing systems are more easi- amount of homophones in Chinese and Sino- ly plagued by this problem than Chinese as the lat- Vietnamese. For example, both ‘明’(bright) and ter may respite the difficulty by assigning different ‘冥’(dark) are read or written as minh with Quốc Chinese characters to respectively record different Ngữ, thus only using Chinese character can one meanings of the same pronunciation. distinguish the two contradictory meanings of the word "minh". 4.2 Why it is not Chu Nom
4 Chinese Characters but not Chu Nom Chữ Nôm is a system of modified and invented characters modeled loosely on Chinese characters, 4.1 Why it is Chinese Characters which, unlike the system of Chinese character (chữ A Chinese character is regarded as a unity of form Hán), allows for the expression of purely Viet- (writing), sound (phonetics) and meaning (seman- namese words to any extent. tics). An illustrative example of Chinese character The character set for Chữ Nôm is extensive, up is given in Figure 3, which demonstrates a charac- to 20,000, arbitrary in composition and inconsis- 2 ter with written form ‘福’, sound ‘fú’(pinyin) and tent in pronunciation . The Chữ Nôm charac- meaning ‘good luck’. However, it is not balanced ters can be divided into two groups: those bor- for the three primary factors of Chinese charac- rowed from Chinese and those invented especial- ter. The core functionality of Chinese character ly for Vietnamese. The characters borrowed from is being a meaning unit. In fact, Chinese charac- Chinese are used to represent either Chinese loan ter is neither a good carrier of pronunciation nor words or native Vietnamese words. For the former stable at written forms: different Chinese variants case, the character may have more than one pro- nunciation. For the latter case, the character may be only used phonetically, regardless of the origi- nal standard meaning of it in Chinese. For exam- ple, the Chinese character ‘ 沒’ (méi, means none
2Online resources on Chữ Nôm can be found at Figure 3: Chinese character is a trinity. the following links, http://nomfoundation.org/ and http://www.chunom.org/.
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Vietnamese Vietnamese Chinese Chinese Chinese Meaning words characters pinyin meaning method phương tiện 方便 fang¯ biàn convenience office building văn phòng 文房 wén fáng study room rich phong lưu 風流 feng¯ liú romantic full-grown phương phi 芳菲 fang¯ fei¯ flowers and plants
Table 3: A list of Sina-Vietnamese words with same writing but different meaning
we will have a Vietnamese text written with Chi- nese characters. Then, with additional processing, the Chinese character sequences in the Vietnamese grammar are converted into grammatical Chinese sentences. The proposed approach is divided into two stages as the following. Stage 1: Syllable-to-Character Conversion To find a matching Chinese character for a Viet- Figure 4: The 20 most frequent Nom characters in namese syllable, bilingual dictionaries are nec- which red bold ones are not used in Chinese. essary to provide possible character candidates. However, we still need more heuristics to deter- in Chinese) is used to represent the Vietnamese mine which character should be chosen according word một (means one in Vietnamese). to the context in which the Vietnamese syllable is Figure 4 shows top 20 most frequent Nom char- located. As multisyllable Vietnamese word usu- acters. As we are finding a pivot written form ally has a unique Chinese equivalent, we propose for Vietnamese to Chinese MT, Chữ Nôm look- to first perform word segmentation over the Viet- s like a good candidate. However, three reasons namese sentence and then convert the segmented make Chữ Nôm unable to fulfill the task. First, words into Chinese. Relying on a pre-specified too many characters in Chữ Nôm belong to the dictionary, the maximum matching algorithm as Vietnamese-only type, which can be neither rec- shown in Algorithm 1 that is traditionally used ognized by modern Chinese nor naturally mapped for Chinese word segmentation will be applied to 3 to commonly used Chinese characters. Second, Vietnamese word segmentation . Chinese characters that are still popularly used in Two bilingual dictionaries are used for Viet- modern Chinese may be only phonetically bor- namese word segmentation and Chinese character rowed by Chữ Nôm. Third, Chữ Nôm has nev- conversion. er been standardized, which may lead to multiple The first dictionary is a Sino-Vietnamese vo- writing choices for the same Vietnamese syllable. cabulary. Sino-Vietnamese vocabulary will play a core role during the conversion. For all known 5 The Proposed Approach Sino-Vietnamese words, we can simply determine their Chinese character equivalents without ambi- Chinese character is a powerful representation as guities. Vietnamese and Chinese actually share the an ideographic writing system, for text written same words on the Sino-Vietnamese vocabulary, with Chinese characters, even if grammatically in- and the only difference is behind the written form- correct, it is understandable and even readable for s, either Vietnamese Quốc Ngữ or Chinese char- people who know Chinese characters but speak d- acters. In this work, we use all bisyllable Sino- ifferent languages of Sinosphere. Vietnamese as Vietnamese vocabulary from (LUO, 2011), which an analytical language, its individual syllable has includes 10,900 Vietnamese-Chinese word pairs. similar ideographic property. Vietnamese is per- This dictionary will be referred to Ds hereafter. haps more suitable to adopt an ideographic writ- For the part beyond the Sino-Vietnamese word- ing system like Chinese characters. Therefore, we s in Vietnamese text, there is no such a dictio- first attempt to find a proper Chinese character to record each syllable of Vietnamese text in accor- 3This algorithm is more precisely referred to as the for- dance with its contextual meaning. In this way, ward maximal matching algorithm.
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Algorithm 1 Maximal matching algorithm dictionary, it will be automatically converted into 1: INPUT1 Dictionary D = {wi|}, and maxlen Chinese characters according to the correspond- is the maximal word length inside D. ing Chinese part of the dictionary. The Sino- 2: INPUT2 Syllable sequence c0c1..cn−1 Vietnamese dictionary Ds is first adopted. If there 3: Let i=0 are still undetermined parts in the sentence after 4: while i
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Systems Ours/Stage 1 Ours/Stage 1+2 Google Systems Ours/Stage 1 Ours/Stage 1+2 Google BLEU 14.5 18.6 20.3 /wo ref. 68.5 72.9 69.3 /w ref 66.1 71.6 67.7 Table 5: BLEU scores for the proposed system. Table 7: Understanding rates with limited Vietnamese Systems Ours/Stage 1 Ours/Stage 1+2 Google knowledge. /wo ref. 65.4 67.1 62.3 /w ref 62.3 63.6 60.7 Systems Sentences Source Du khách Tây Ban Nha thưởng thứ trà tại Trâm Anh quán. Table 6: Understanding rates without any Vietnamese Target 西班牙游客在簪缨馆品茶。 knowledge. Stage 1 游客 西班牙 赏识 茶 在 簪缨 店 . Stage 2 西班牙 游客 赏识 茶 在 簪缨 店 . from 1993 to 1997. To segment the Chinese tex- Google 西班牙游客享受茶在英国的前哨基地。 t, the maximal matching segmentation algorithm with Chinese side words of the above two bilin- Table 8: Vietnamese-to-Chinese translation. gual dictionaries are used. The results with Google translation comparison nese that Vietnamese is a head-initial language. are given in Table 5. With limited support linguis- The results are given in Table 7. The second group tic resources, the proposed approach gives a very of human evaluation results are slightly better than competitive result as the Google translator does. the first group. With limited linguistic knowledge, Although it goes without saying, actually all the human evaluator can finish the necessary grammar state-of-the-art MT systems are far from the re- conversion by himself for better understanding on quirement of being serious publishing or any of- the translated text. ficial usages. Most of the current MT outputs are Overall, the proposed approach gives satisfac- used, tacitly in fact, for a rough understanding of tory results on Vietnamese to Chinese translation texts written in other languages that readers do not with quite limited linguistic input. Our system know at all. We will evaluate the results of the gives competitive results as the existing system proposed approach from this sense. A group of in terms of BLEU, and outperforms the latter ac- human evaluation experiments are done based on cording to the newly introduced evaluation metric. the following scoring rules. For each translated These comparisons show that though the transla- sentence, a human evaluator will determine if the tion output of our system is not up to its best on rough meaning of the sentence is understandable, word transformation and ordering (that is mostly and the sentence will be given score (1) 1.0 if the concerned by the BLEU score, and mostly deter- sentence can be fully understood; (2) 0.5 if the sen- mined by grammar translation stage.), but it pos- tence seems understandable but not so certain; (3) sesses better understandability, which is mostly 0.0 if the meaning of sentence cannot be captured determined by semantic translation stage. at all. We define understanding rate for the given ∑N 7 Error Analysis αi i=1 test set, Ur = N , where N is number of sen- Rough manual inspection shows that both work tences in the test set and αi is the evaluation score stages introduce factors that lead to poor transla- given to the i-th sentence. tion. For Stage 1, most errors occur because the The first group of results with Ur are given in target Chinese characters are incorrectly given by Table 6. There are two types of results in the ta- the dictionary Dg at the very beginning. For those ble, the first human evaluator gives score without Vietnamese syllables that have multiple conver- allowing to read the translation reference, while sion options in writing as Chinese characters, it is the second is allowed to read the reference to ver- surprising that we find few examples on such type- ify and modify his score after he already gives a s of character selection errors. This observation score. suggests that a direct refine work on Dg may be The second group of results are given on the hopeful to give significant performance improve- condition that human evaluators are taught about ment. Furthermore, it is also useful to enrich the grammar difference between Vietnamese and Chi- current Sino-Vietnamese dictionary Ds as up to
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now it only includes bisyllable words. A simple maximal matching algorithm with For Stage 2, it looks like that word order ad- bilingual dictionaries can be adopted to perform justing does not work well, though one can see semantic translation as Stage 1 because two essen- a BLEU score increasing after the processing of tial language facts, (1) Vietnamese and Chinese Stage 2. In fact, Ur scores in Table 6 and 7 demon- share a very large vocabulary, and (2) They both strate that word order only has a marginal effect belong to analytic (isolating) languages, which over the understanding (or guessing) the translat- means that there is nearly a full correspondence ed sentence. Later, according to word order dif- between a single word/character/syllable and a s- ference between Chinese and Vietnamese, we may ingle aspect of meaning. Motivated by this obser- especially adjust the order of Vietnamese words vation, it is possible to extend this work to oth- with specific part-of-speech so that the translation er languages in Sinosphere, such as Korean and results can be further improved. Japanese. The following gives reasons why both Table 8 shows an actual translation output by languages meet the above conditions. our system. For a detailed English explanation, Let us first consider the vocabulary. The exac- please refer to the appendix. t proportion of Sino-Korean vocabulary is still a matter of debate. (Sohn, 2001) stated that it is be- 8 Semantic Translation vs. Grammar tween 50–60%. For Sino-Japanese, it usually has Translation an estimation of 40-50%. Both Korean and Japanese belong to agglutina- Using Chinese character as an intermediate for- tive languages, which seems that the above sec- m, a two-stage MT approach has been proposed. ond condition is not met. However, using Chi- We loosely refer the first stage as semantic transla- nese character based writing traditionally or cur- tion, and the second as grammar translation. The rently, a stable correspondence between meaning semantic translation is called because syllable to and writing for both languages can be generally character conversion is based on semantic equiv- found 8. From the writing perspective, both Kore- alence rather than anything else, such as phonet- an and Japanese are quite isolating. ics or written forms. The grammar translation in- cludes two monolingual subtasks, word restating 10 Conclusions and Future Work and reordering, to let the expression more fluent. This paper presents a two-stage conversion method Standard SMT integrates semantic and gram- for the MT task between resource-scarce language mar translation into one word/phrase alignmen- pairs that both belong to the isolating language t model, which partially make researchers work- type, such as Vietnamese and Chinese, and other ing on MT lose focus. We say that the proposed languages in Sinosphere that demonstrate observ- two-stage MT processing strategy allows transla- able isolating language characteristics. tion research more focused. For example, our ex- Chinese character as the heart of the evolution periments demonstrate a higher understanding rate of languages in Sinosphere is selected as an inter- but lower BLEU score for the same MT outputs. mediate equivalent form during translation. In de- If we loosely regard that understanding rate mea- tail, Chinese character sequences subject to source sures the semantic aspect of MT performance and language grammar play a pivot role. Compared to BLEU measures the grammar factor, then we now existing translation system, the proposed method, have a chance to see that a poor grammar transla- with a small number of linguistic resources, gives tion is an obstacle on the way to let MT outputs competitive or even better results in terms of s- become really useful on a formal occasion. tandard BLEU score or a newly introduced human 9 Other Language Pairs evaluation metric, understanding rate. It is worth noting that we have only made a very Now we consider if the proposed approach can be preliminary attempt with respect to the proposed extended to other language pairs. Though it is a approach. For example, during semantic trans- two-stage translation, language specific properties lation, in addition to bilingual dictionary, we do are actually concerned only at Stage 1, and Stage 8For example, though the meaning moutain is pronounced 2 may work on any other target language in prin- as yama or san in Japanese, it can be always written as the ciple. Thus we may only focus on Stage 1. same Chinese character 山.
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not use any other context information to effective- Manh Hai Le and Thi Tuoi Phan. 2010. Lexical gap ly determine the target Chinese characters. During in English-Vietnamese machine translation: What grammar translation, we do not use any language- to do? In 2010 International Conference on Asian specific features to improve the target language Language Processing, pages 265–269, Harbin, Chi- na, December. generation. Exploring all the potentials, it is ex- Manh Hai Le, Chanh Thanh Nguyen, Chi Hieu N- pected to receive even better results. guyen, and Thi Tuoi Phan. 2006. Dictionaries for English-Vietnamese machine translation. In The References 21st International Conference on the Computer Pro- cessing of Oriental Languages, pages 363–369, Sin- Paul K. Benedict. 1944. Thai, Kadai and Indonesian: gapore, December. A new alignment in southeastern Asia. American Wenqing LUO. 2011. A Study on Bi-syllable Sino- Anthropologist, 44(2):576–601. Vietnamese Words in Vietnamese: A Comparison Peter F. Brown, Vincent J. Della Pietra, Stephen with Chinese (in Vietnamese). World Publishing A. Della Pietra, and Robert. L. Mercer. 1993. Corporation, Guangzhou, China. The mathematics of statistical machine translation: Yanjun Ma and Andy Way. 2009. Bilingually mo- parameter estimation. Computational Linguistics, tivated domain-adapted word segmentation for sta- 19(2):263–311. tistical machine translation. In Proceedings of the Thanh Hung Bui, Le Minh Nguyen, and Akira Shi- 12th Conference of the European Chapter of the As- mazu. 2010. Using rich linguistic and contextual sociation for Computational Linguistics, pages 549– information for tree-based statistical machine trans- 557, Athens, Greece, April. Association for Compu- lation. In 2011 International Conference on Asian tational Linguistics. Language Processing, pages 189–192, Harbin, Chi- James A. Matisoff. 1990. On megalocomparison. na, December. Language, 66(1):106–120. Thanh Hung Bui, Le Minh Nguyen, and Akira Shi- Giang Thanh Nguyen and Dien Dinh. 2012. Improv- mazu. 2012. Sentence splitting for Vietnamese- ing English-Vietnamese word alignment using trans- English machine translation. In 2012 Fourth Inter- lation model. In 2012 IEEE International Confer- national Conference on Knowledge and Systems En- ence on Computing and Communication Technolo- gineering, pages 156–160, Danang, Vietnam, Au- gies, Research, Innovation, and Vision for the Future gust. (RVIF), Ho Chi Minh City, Vietnam, February. Pi-Chuan Chang, Michel Galley, and Christopher D. Thai Phuong Nguyen and Akira Shimazu. 2006. Manning. 2008. Optimizing Chinese word segmen- Improving phrase-based statistical machine transla- tation for machine translation performance. In Pro- tion with morphosyntactic transformation. Machine ceedings of the Third Workshop on Statistical Ma- Translation, 20:147–166. chine Translation, pages 224–232, Columbus, Ohio, Vinh Van Nguyen, Thai Phuong Nguyen, Akira Shi- USA, June. mazu, and Minh Le Nguyen. 2008. A reorder- Chenhui Chu, Toshiaki Nakazawa, Daisuke Kawahara, ing model for phrase-based machine translation. In and Sadao Kurohashi. 2012. Exploiting shared Chi- GoTAL - 6th International Conference on Natural nese characters in Chinese word segmentation opti- Language Processing, pages 476–487, Gothenburg, mization for Chinese-Japanese machine translation. Sweden, August. In Proceedings of the 16th EAMT Conference, pages ThuyLinh Nguyen, Stephan Vogel, and Noah A. Smith. 35–42, Trento, Italy, May. 2010. Nonparametric word segmentation for ma- Christopher Dyer, Smaranda Muresan, and Philip chine translation. In Proceedings of COLING-2010, Resnik. 2008. Generalizing word lattice translation. pages 815–823, Beijing, China, August. In Proceedings of the 46th Annual Meeting of the Quy Nguyen, An Nguyen, and Dien Dinh. 2012. An Association for Computational Linguistics: Human approach to word sense disambiguation in English- Language Technologies, pages 1012–1020, Colum- Vietnamese-English statistical machine translation. bus, OH, USA. In 2012 IEEE International Conference on Comput- Thi My Le Hoang, Thi Bong Phan, and Huy Khanh ing and Communication Technologies, Research, In- Phan. 2012. Building a machine translation sys- novation, and Vision for the Future (RVIF), Ho Chi tem in a restrict context from Ka-Tu Language into Minh City, Vietnam, February. Vietnamese. In 2012 Fourth International Confer- Thien Giap Nguyen. 2008. A Brief History on Viet- ence on Knowledge and Systems Engineering, pages namese Study (in Vietnamese). Vietnam Education 167–172, Danang, Vietnam, August. Press, Hanoi, Vietnam. Manh Hai Le and Thi Tuoi Phan. 2009. Three algo- Franz Josef Och and Hermann Ney. 2003. A sys- rithms for word-to-phrase machine translation. In tematic comparison of various statistical alignmen- 2009 International Conference on Asian Language t models. Computational Linguistics, 29(1):19–51, Processing, pages 328–331, Singapore, December. March.
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Kishore Papineni, Salim Roukos, Todd Ward, and Wei- English Vietnamese Chinese Stage√ 1 Jing Zhu. 2002. BLEU: a method for automat- tourist du khách 游客 √ ic evaluation of machine translation. In Proceed- Spain Tây Ban Nha 西班牙 ings of the 40th Annual Meeting on Association for enjoy thưởng thứ 赏识 √? Computational Linguistics, ACL ’02, pages 311– tea trà 茶 √ 318, Stroudsburg, PA, USA. Association for Com- at tại 在 √ putational Linguistics. Tram Anh Trâm Anh 簪缨 Michael Paul, Andrew Finch, and Eiichiro Sumita. house,inn,etc quán 店 ? 2010. Integration of multiple bilingually-learned segmentation schemes into statistical machine trans- Table 9: Vietnamese-to-Chinese translation: word by lation. In Proceedings of the Joint 5th Workshop on word conversion. Statistical Machine Translation and MetricsMATR, pages 400–408, Uppsala, Sweden, July. Association for Computational Linguistics. first word thưởng thứ is Sino-Vietnamese, its exact 赏识 Son Bao Pham, Giang Binh Tran, Dang Duc Pham, Chinese form is right ‘ ’. Unfortunately, these Kien Chi Phung, and Kien Trung Nguyen. 2009. two characters in Chinese as a word means ‘appre- An information extraction approach to English- ciate’ instead of ‘enjoy’ as its Vietnamese coun- Vietnamese weather bulletins machine translation. terpart. Furthermore, Stage 2 also fails to recti- In 2009 First Asian Conference on Intelligent In- fy this meaning-drift word due to the limitation of formation and Database Systems, pages 161–166, our synonymous dictionary. However, if we only Dong hoi, Quang binh, Vietnam, April. concern about the first character ‘赏’ of the word Ho-Min Sohn. 2001. The Korean Language. Cam- ‘赏识’, it will be acceptable for Chinese readers, as bridge University Press, Cambridge, UK. two basic senses of ‘赏’ are ‘enjoy’ and ‘award’, Hong-Nhung Nguyen Thi and Dien Dinh. 2008. 赏茶 A syntactic-based word re-ordering for English- though ‘ ’ is not a usual expression in Chinese Vietnamese statistical machine translation system. for saying ‘enjoy tea’. The second inexact conver- In The Tenth Pacific Rim International Conference sion about ‘quán’ comes from building the second on Artificial Intelligence (PRICAI-08), pages 809– bilingual dictionary Dg. As in the aligned phrase 818, Hanoi, Vietnam, December. table, ‘quán is translated onto ‘店’(diàn in Chi- Masao Utiyama and Hitoshi Isahara. 2007. A com- nese pinyin, means ’shop’ or ‘building/facilities parison of pivot methods for phrase-based statistical for business purpose’) with a higher probability machine translation. In Proceedings of NAACL HLT than the expected exact one, ‘ 馆’(guan,ˇ means 2007, pages 484–491, Rochester, NY, USA, April. building (group) for specific purpose). Though the Hua Wu and Haifeng Wang. 2009. Revisiting pivot 店 language approach for machine translation. In Pro- character ‘ ’ is not the expected translation, it is ceedings of the 47th Annual Meeting of the ACL and rough in line with the original meaning of source the 4th IJCNLP of the AFNLP, pages 154–162, Sin- phrase and acceptable for most Chinese readers. gapore, August. Generally, most Vietnamese names are supposed Ning Xi, Guangchao Tang, Xinyu Dai, Shujian Huang, to have standard forms written in Chinese charac- and Jiajun Chen. 2012. Enhancing statistical ma- ters. Using a pivot language, Vietnamese names chine translation with character alignment. In Pro- are hard to exactly be translated into Chinese. For ceedings of the 50th Annual Meeting of the Associa- our example, in addition to the unique mismatched tion for Computational Linguistics, pages 285–290, character, the named entity Trâm Anh quán has Jeju, Republic of Korea, July. Jia Xu, Jianfeng Gao, Kristina Toutanova, and Her- been exactly translated, which can be hardly done mann Ney. 2008. Bayesian semi-supervised chine- by Google translator, as we surmise, using English seword segmentation for statistical machine transla- as a pivot language. In fact, the meaning of the tion. In Proceedings of COLING-2008, pages 1017– Google translator output is ‘Spanish tourists enjoy 1024, Manchester, UK, August. tea at the British outpost’. Overall, by speculating that ‘ 赏识茶’ is a typo APPDENDIX of ‘ 赏茶’, a Chinese reader can easily guess the We now give a detailed English explanation to true meaning of the source Vietnamese, ‘西班牙 the translation example output by our system. A 游客在簪缨馆赏茶(Spanish tourists enjoy tea at word-by-word translation is shown in Table 9. The Tram Anh shop)’ from the translation given by our meaning of source Vietnamese is that ‘Spanish system, ‘西班牙游客赏识茶在簪缨店(Spanish tourists enjoy tea at Tram Anh teahouse.’ We ana- tourists appreciate tea at Tram Anh shop)’. lyze two problematic words in our translation. The
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