The following relates to the linguistic arts. It finds particular application in conjunction with translation of text from a source language to a target language, and will be described with particular reference thereto. However, it is to be appreciated that the following is also amenable to other like applications, such as electronic foreign language learning tools.
A common problem in the authoring of text translations is the “tip of the tongue” problem. The author is proceeding apace in writing the translation, but comes up against a word or phrase in the source language which is unfamiliar to the author, or which the author is unable to effectively express in the target language.
To address this problem, the author may consult a bilingual dictionary, which may be in either paper or electronic form. In either case, the author must stop work and access the bilingual dictionary. A heavily abridged bilingual dictionary may not suffice, since the “tip of the tongue” problem typically arises in non-standard situations such as collocations, idiomatic phrases, and so forth. Such complex or non-standard forms are sometimes omitted from abridged dictionaries, and so a fairly comprehensive bilingual dictionary should be consulted.
A comprehensive bilingual dictionary has extensive entries for each word, typically including a substantial number of example source language contexts and corresponding target language translations, collocations, and so forth. If a word has more than one meaning or can be used as more than one part of speech, then each possible usage is extensively detailed. Still further, the author may need to consult several entries if the untranslated portion is a phrase including several words. Such searching can become time consuming and burdensome for the author.
The following copending, commonly assigned applications: Bi-Dimensional Rewriting Rules for Natural Language Processing (Xerox ID 20040117-US-NP, Ser. No. 11/018,892 filed Dec. 21, 2004) and Retrieval Method For Translation Memories Containing Highly Structured Documents (Xerox ID 20031674-US-NP, Ser. No. 11/018,891 filed Dec. 21, 2004) are herein incorporated by reference.
In accordance with one aspect, a bilingual authoring apparatus is disclosed. A user interface is provided for inputting partially translated text including a text portion in a source language and surrounding or adjacent text in a target language. A bilingual dictionary associates words and phrases in the target language and words and phrases in a source language. A context sensitive translation tool communicates with the user interface, receives the partially translated text, and provides at least one proposed translation in the target language of the text portion in the source language. The at least one proposed translation in the target language is derived from the bilingual dictionary based on contextual analysis of at least a portion of the partially translated text.
In accordance with another aspect, a bilingual authoring method is provided. Partially translated text is received from an associated user. The partially translated text includes a text portion in a source language and surrounding or adjacent text in a target language. The partially translated text is identified. At least one proposed translation in the target language of the text portion in the source language is derived based on contents of a bilingual dictionary and contextual analysis of at least a portion of the partially translated text. The at least one proposed translation is displayed to the associated user.
In accordance with yet another aspect, a storage medium stores instructions which when executed by an electronic processor perform a method including: (i) receiving partially translated text including a text portion in a source language and surrounding or adjacent text in a target language; and (ii) deriving at least one proposed translation in the target language of the text portion in the source language based on contents of a bilingual dictionary and contextual analysis of at least a portion of the partially translated text.
With reference to
As the author works, he or she may encounter a “tip of the tongue” problem, in which the author comes up against a word or phrase in the source language which is unfamiliar to the author, or which the author is unable to effectively express in the target language. In such a situation, the author suitably inputs the untranslated text in the source language within the context of the target language authored text, and calls up an authoring assistant 30. The invoked authoring assistant 30 runs concurrently with the authoring software 20 at least when invoked so as to provide suggested translations in the target language for the entered text in the source language.
If the text in the source language is a phrase or other sequence of words or tokens providing context, the authoring assistant 30 includes or accesses a semantic dictionary lookup module 32 that references a bilingual lexicon or dictionary 34 to perform a contextual lookup of the text in the source language. The contextual lookup determines one or more likely translations of the phrase in the source language. The authoring assistant 30 communicates these one or more proposed translations to the author, for example via the display 12.
The semantic dictionary lookup module 32 performs monolingual lexical, syntactic, and semantic analysis of the phrase in the source language in order to determine one or more proposed translations in the target language. Typically the semantic dictionary lookup module 32 parses the phrase with reference to source language entries of the dictionary 34. The parsing breaks the phrase into tokens representative of words, punctuation, or the like, and determines parts-of-speech and optionally also higher order categorizations for each of the tokens using syntactic analysis employing a monolingual grammar typically described by rewriting rules descriptive of common combinations of parts of speech or higher order categories. The parsing is optionally also augmented by limited semantic analysis, such as identification of collocations listed in the lexicon or dictionary 34. Based on the parts-of-speech and optional higher order token categorizations, the semantic dictionary lookup module 32 determines likely translations in the target language using example context translations or other semantic information contained in the bilingual lexicon or dictionary 34.
The semantic dictionary lookup module 32 can have varying levels of functionality, and can be embodied by various semantic dictionary lookup systems and methods. In some embodiments, for example, the semantic dictionary lookup module 32 employs functionality set forth in U.S. Pat. No. 5,642,522 issued to Zaenon and Karttunen and in “LOCOLEX: Translation Rolls off Your Tongue.” F. Segond, D. Bauer, and A. Zaenen, proceedings of ACH-ALLC 95, Santa Barbara, USA, July 1995. This functionality matches complete monolingual phrases in the source language to propose translations in the target language, using a combination of lemmatization, part of speech disambiguation, and multiword phrase matching techniques. The multi-word phrase matching of these approaches is restricted to “idiomatic expressions” or part of speech disambiguation.
In other embodiments, the semantic dictionary lookup module 32 is embodied by a version of the Xerox semantic dictionary lookup, which is available from Xerox Research Centre Europe (XRCE, located in Grenoble, France). This approach uses information available in dictionaries including collocation information, examples of usage of the word, and so forth, to perform a lookup of a word relative to its context and to perform disambiguation. A similar semantic dictionary lookup method is described in U.S. Pat. No. 6,405,162 issued to F. Segond and C. Brun.
The semantic dictionary lookup module 32 combines semantic, syntactical, and lexical analyses of the text in the source language in a monolingual fashion to determine the likely meaning of the words in the source language phrase, and employs translations provided by the bilingual dictionary to come up with proposed translations in the target language. A multiple word or multiple token phrase in the source language provides sufficient context to perform the syntactic and semantic analyses monolingually in the source language.
In some cases, however, the text in the source language consists of a single word or token that does not provide sufficient context to perform monolingual syntactic and semantic analysis in the source language. In such cases, the semantic dictionary lookup module 32 cannot directly process the word or token, beyond providing lexical information in the form of a typically lengthy entry for the word or token contained in the bilingual dictionary. A lengthy lexicon entry is difficult to display on the limited area of the display 12, and the large amount of displayed information limits the usefulness of the lengthy lexicon entry to the author.
Accordingly, the authoring assistant 30 performs syntactic and semantic analysis of surrounding or adjacent text authored in the target language, and uses that contextual information to propose one or more target language translations for the single word or token in the source language. Toward this end, the authoring assistant 30 includes or accesses a parser 38 to parse the surrounding or adjacent text authored in the target language using a suitable target language grammar. During the parsing, the word or token in the source language is treated as an unknown token. Such parsing may enable the part-of-speech of the word or token in the source language to be guessed partially or even unambiguously identified. In some cases, unambiguous identification of the part of speech by itself may enable proposal of an unambiguous target language translation of the word or token.
In other cases, the parsing by itself is insufficient to provide a sufficiently short list of one or more translations for proposal to the author. In these cases, a text matching module 40 compares the surrounding or adjacent text in the target language with translations of semantic examples provided in the bilingual dictionary 34 in an attempt to identify a match. If such a match is found, then the target language translation of that semantic example is proposed to the author as a possible translation. In some embodiments, the text matching module 40 further accesses the bilingual lexicon or dictionary 34 to identify synonyms in the target language for words in the translations of the semantic examples given in the dictionary 34, thus expanding the available semantic data for comparison. In a similar fashion, a collocation matching module 42 of the authoring assistant 30 compares translations in the source language of surrounding or adjacent words of the authored text with lexical or semantic collates identified in the bilingual lexicon or dictionary 34; successful collocation matches provide additional proposed translations.
The authoring assistant 30 illustrated in
With reference to
At this point, the author invokes the authoring assistant 30 to provide proposed translations for the French text portion 52: “abandonner les recherches.”To do so, the author uses the mouse 16, keyboard 14, or other input device to mark the French text portion 52: “abandonner les recherches” by highlighting 54 (diagrammatically indicated in
In the embodiment illustrated in
The invoked authoring assistant 30 recognizes the French text portion 52 as a multiple-word phrase providing substantial contextual information in the French language. Accordingly, the authoring assistant 30 passes the French text portion 52 to the semantic dictionary lookup module 32, which in turn accesses the bilingual lexicon or dictionary 34 to locate the entry for “abandoner”. In the example embodiments described herein, the bilingual dictionary 34 employed is the Oxford-Hachette Bilingual dictionary (Correard M.-H., Grundy V., Eds., Oxford-Hachette French Dictionary, Oxford-Hachette, Paris, 1994); however, substantially any electronic bilingual lexicon or dictionary supporting at least the source and target languages can be employed.
In
With reference to
With reference to
If the decision operation 82 identifies the expression in the source language as multi-word, a semantic dictionary lookup is performed in a process operation 84. This operation 84 is performed by forwarding the text portion in the source language 52 to the semantic dictionary lookup module 32 to perform the semantic analysis. The one or more proposed translations returned by the semantic dictionary lookup module 32 are presented to the user in process operation 86, for example by displaying them on the screen using one of the formats shown in
On the other hand, if the decision operation 82 identifies the expression in the source language as a single word, then a monolingual semantic dictionary lookup is not particularly helpful in view of the lack of context in the source language. Accordingly, in a process operation 90 the authoring assistant 30 finds possible translations based on the context provided by the surrounding or adjacent text in the target language, and proposes one or more such translations to the user in the process operation 86.
Having described a suitable processing flow for the authoring assistant 30, some examples of operation on multi-word expressions is described.
With reference to
In another example, the semantic dictionary lookup module 32 provides a semantic matching, according to an ontology, in a case where a lexical match wasn't performed. Consider the example authored text:
The context of the lookup is restricted to the source language phrase 52′ that the author has typed in, and this is a small context. Since semantic dictionary lookup algorithms typically use examples and collocates of a dictionary to build the rules, they are particularly well suited to be applied on such small contexts.
In cases where the source language expression is a single word, there is no context for a monolingual semantic analysis performed in the source language. Accordingly, in such cases the decision operation 82 directs processing to the process operation 90 which finds possible translations based on the context provided by the surrounding or adjacent text in the target language.
With reference to
On the other hand, if the process operation 102 is unable to make any matches, then the decision operation 104 passes flow to a collate matching process operation 110. In the collate matching process, the collocation matching module 42 translates authored words in the target language back into the source language, and compares these translations with source language collates of the source language word 52′ identified in the bilingual dictionary 34. The comparison can be purely lexical (comparing the literal dictionary entry with the translation of the surrounding context) or can include a semantic component by incorporating synonyms of the surrounding or adjacent words. If the collate matching process operation 110 identifies potential translations, these are proposed to the author in the process operation 86.
The processing 90 applies to a source language expression consisting of a single word. By single word, it is meant that the expression is restricted to one word of category Noun, Adjective, Adverb or Verb, ignoring the stop words. Having provided a general overview of suitable processing 90 performed by the authoring assistant 30 respective to a single word in the source language, some specific examples are next provided.
Consider the following partially translated text:
As another example, consider the following partially translated text:
As another example, consider the following alternative sentence containing the French word “considerer”:
As another example, consider the following partially translated text:
As another example, consider the following partially translated text:
If the ontologies in the source (e.g., French) and target (e.g., English) languages are built according to the same hierarchy of semantic classes (for example, using Word Net and EuroWordnet), the translation of the collocates can be bypassed, and the collate matching 110 can perform the match at the semantic level using these parallel ontologies.
While particular embodiments have been described, alternatives, modifications, variations, improvements, and substantial equivalents that are or may be presently unforeseen may arise to applicants or others skilled in the art. Accordingly, the appended claims as filed and as they may be amended are intended to embrace all such alternatives, modifications, variations, improvements, and substantial equivalents.
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Number | Date | Country |
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Number | Date | Country | |
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20060136223 A1 | Jun 2006 | US |