Customizable machine translation service

Description

CROSS-REFERENCES

The present application is related to U.S. patent application Ser. No. 11/223,823 filed Sep. 9, 2005 and entitled “Adapter for Allowing Both Online and Offline Training of a Text to Text System”; U.S. patent application Ser. No. 10/143,382 filed May 9, 2002 and entitled “Statistical Memory-Based Translation System”; and U.S. patent application Ser. No. 11/635,248 filed Dec. 5, 2006 and entitled “Systems and Methods for Identifying Parallel Documents and Sentence Fragments in Multilingual Document Collections,” all of which are herein incorporated by reference.

BACKGROUND

1. Field of Invention

The present invention relates generally to machine translation and more specifically to providing a customizable machine translation service.

2. Description of the Related Art

Machine translation techniques, including translation memories, statistical machine translation, linguistic models, and the like, typically require a training corpus or other pre-translated materials on which to base translations. This data set is typically very large and based on generic documents. Further, due to the size of the data set required, the translations typically reflect generic word usage or word usage in commonly-translated domains such as news, government documents, and the like.

Currently, online machine translation services are mostly generic (i.e., they are meant to translate texts in any given domain). For example, SDL, a provider of translation services, offers an online translation service at www.FreeTranslation.com. At this website, a user can enter an input text string in a source language and specify a target language. The translation service will translate the input text string into the specified target language and display an output string. However, this service and other similar services are not equipped to manage and exploit specialized translations.

Some translation memories are available online. For example, Wordfast provides a Very Large Translation Memory (VLTM) that can be accessed using a client. However, this project requires users to donate translation memories in order to expand. Further, domains are not separated from one another within the translation memory. Lingotek offers an online language search engine onto which users may upload translated content and later search for segments of the translated content.

Specialized translations typically include translations of documents generated by a niche or specialty. Technical documents generated within a niche often require specialized translations that require a translation engine to be trained on a specialized training set. For example, an automotive manufacturer may require translations of documents that use otherwise generic words in an atypical manner. An information technology supplier may use the same words in yet another manner. As such, there is a need for a translation service capable of being tuned/trained to a specialty/niche and equipped to manage and exploit specialized translations.

SUMMARY

A system and method for providing a translation service is provided. The exemplary method comprises providing a translation interface accessible via a network such as the Internet. The translation interface receives specialized data associated with a domain from a member. On the basis of this data, a domain-based translation engine or translation memory is made available. A text string written in a source language is received from the member via the translation interface. A previously developed domain-based translation engine is selected. In exemplary embodiments, the domain-based translation engine may be associated with a source language, a target language, and a domain. The text string may be translated into the target language using, at least in part, the selected domain-based translation engine. The translated text string may then be transmitted to the member via the Internet.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a networked environment in which various embodiments may be practiced;

FIG. 2 is a block diagram of a domain-based translation engine according to an embodiment of the present invention;

FIG. 3 is a block diagram of a customization engine according to an embodiment of the present invention;

FIG. 4 is a block diagram of a translation memory engine according to an embodiment of the present invention.

FIG. 5 is a flowchart of an exemplary process for generating a translation engine; and

FIG. 6 is a flowchart of an exemplary process for providing a translation service.

DETAILED DESCRIPTION

A service for providing specialized translations enables members associated with a specialized niche to use previously translated documents without having to purchase and install a translation engine on a local server. A translation engine is configured to translate an input text string written in a source language into a target language. In some embodiments, the translation engine may perform statistical machine translation (SMT) or another data-driven machine translation. Data-driven machine translations may include translation memory, heuristics-based, context-based, linguistics-based, a hybrid translation technique, or the like. The member may provide any amount of specialized data associated with a domain and/or language pair. The specialized data may be used as a translation memory or as training data in a data-driven machine translation engine. The member may select a translation engine and/or translation memory that the specialized translation service uses to translate an input string.

If the specialized translation service is based on a small amount of specialized data, the data may be used to generate a translation memory that can be accessed by the translation engine. In some embodiments, the translation memory may be returned to the user. If there is a large amount of specialized data, a customized translation engine may be generated. In some embodiments, the customized translation engine may be a data-driven translation engine trained on both a generic data set and the specialized data.

FIG. 1 depicts a networked environment 100 in which various embodiments of the present invention may be practiced. The environment 100 comprises a plurality of members 102A through 102N, and a translation service system 104 which comprises a plurality of domain-based translation engines 106A and 106B, a customization engine 108, and/or a translation memory engine 110 communicatively coupled via a network 112. The network 112 may comprise a private network and/or a public network. In some embodiments, the network 112 comprises the Internet. Any number of members 102 may be present in the environment 100.

The members 102A through 102N provide specialized data and/or input strings to be translated. For example, member 102A may be an automotive manufacturer while member 102N may be an information technology supplier. In exemplary embodiments, the member 102A may provide repair manuals that are previously translated into one or more target languages as specialized data. The member 102N may, however, provide no specialized data. Any member 102A through 102N may provide an input text string to one of the domain-based translation engines 106. In some embodiments, the member 102A may select multiple domain-based translation engines 106 if a plurality of domain-based translation engines 106 is available.

The translation service system 104 may comprise the plurality of domain-based translation engines 106, the customization engine 108, and/or the translation memory engine 110. The translation service system 104 may provide an online translation service, generate a customized domain-based translation engine, and/or generate a translation memory. The translation service system 104 may comprise one or more servers or other computing devices configured to communicate over the network 112 via a communications interface. The server(s) may comprise a processor configured to execute programs stored in a memory.

In some embodiments, member 102 may select whether to generate a translation memory and/or a domain-based translation engine using specialized data. If generating a translation memory is selected, the member 102 may receive the translation memory from the translation memory engine 110 and store the translation memory. The member may additionally transmitto or select a translation memory from the translation service system 104 from which a domain-based translation engine may be generated.

The translation service system 104 may provide a translation interface via, for example, a website. The translation interface may be configured to receive specialized data from the members 102A through 102N. Based on the amount of specialized data received and the instructions received from the member, the translation service system 104 may determine whether to generate a translation memory using the translation memory engine 110 and/or use the customization engine 108 to create a domain or member-specific translation engine, such as domain-based translation engine 106A.

In some embodiments of the present invention, the translation service system 104 may comprise an accounting engine (not shown). The accounting engine may calculate credits and/or debits based on the activities of members 102A through 102N. The member 102A may be associated with an account having a number of credits or debits based on usage. The debits may be charged in any way including pay-per-use, subscription, packages, and the like. For example, the member 102A may purchase a subscription for access to one or more domain-based translation engines 106. In another embodiment, the member 102A may pay a fee for services requested. Any combination and/or variation of billing may be used.

Various embodiments of the translation service system 104 may grant a credit to the member 102A. For example, if the member 102A provides specialized data that is accessed to translate an input string received from member 102N, the member 102A may receive a credit for future translations and/or currency. The specialized data may be associated with a translation memory and/or a domain-based translation engine 106 as discussed further herein.

The domain-based translation engine 106A comprises a translation engine that may be selected by the member 102A. The domain-based translation engine 106A may be associated with a language pair and/or a domain. A language pair is a pairing of two languages one of which is a source language and the other of which is a target language. In some embodiments, the language pair is bi-directional such that the source language may become the target language and vice versa. The domain is any specialty or niche that has some jargon or specialized usage of words. Domains may include, for example, information technology, automotive, literature, medicine, law, or the like. Additionally domains may be of any scope. For example, a domain may relate specifically to a product, such as a video game system or console. The domain-based translation engine 106A is configured to translate an input string associated with the domain from a source language into a target language. As such, the language pair may comprise any source language and any target language. The domain-based translation engine 106A may use no specialized data, or any amount of specialized data. The specialized data may also be used by the translation memory engine 110 to generate a translation memory that can be accessed by the domain-based translation engine 106A. The environment 100 may comprise a plurality of domain-based translation engines 106A and 106B.

The customization engine 108 is configured to process a large amount of specialized data to generate a domain-based translation engine 106 or a translation memory associated with the member 102A or a domain. In some embodiments, the customization engine 108 may generate a set of domain-specific parameters and merge the generated set of domain-specific parameters with a generic set of parameters. The customization engine 108 may, for example, receive a large amount of translated repair manuals from an automotive manufacturer. The translated auto repair manuals may be used to then generate a domain-based translation engine 106A specific to the automotive manufacturer and/or automotive repair manuals.

The translation memory engine 110 may generate a translation memory based on the specialized data. In some embodiments, the translation memory may be used to train a domain-based translation engine 106A. The translation memory may also be accessed by the domain-based translation engine 106A during translation or accessed by the customization engine 108 to train the domain-based translation engine 106A. In some embodiments, the translation memory may be stored at the member 102.

FIG. 2 is a block diagram of a domain-based translation engine 106A according to an embodiment of the present invention. The domain-based translation engine 106A may comprise a communications module 202 and a translation module 204. The domain-based translation engine 106A may access stored merged parameters in a merged parameters storage device 206 and/or optional translation memory storage device 208. The domain-based translation engine 106A may be associated with a language pair (e.g., English-Chinese) and a domain (e.g., automotive). In some embodiments, the domain-based translation engine 106A is configured to perform bi-directional translations.

The communications module 202 is configured to receive specialized data and/or input text strings from the member 102A. The communications module 202 may process or re-format the specialized data. If the communications module 202 receives an input text string, the communications module 202 may transmit the input text string to the translation module 204.

The translation module 204 is configured to translate the input text string from the source language to the target language. The translation module 204 may be configured to translate the input text string using a variety of data-driven machine translation techniques including heuristics-based, context-based, translation memory-based, linguistic-based, statistics-based, or any combination of these techniques. In the embodiment shown, the translation module 204 is configured to access a set of merged parameters stored in the merged parameters storage device 206 associated with a statistical machine translation system and the translation memory storage device 208. The translation memory may be based on specialized data received from the member 102A. The domain-based translation engine 106 may comprise fewer or additional modules or components according to various embodiments including modules for performing other types of data-driven machine translations.

The merged parameters storage device 206 stores merged parameters that comprise information derived from a set of generic training data and specialized data associated with the domain. The generic training data may be derived from parallel or comparable bilingual data such as translation memories, probabilistic and non-probabilistic word-based and phrase-based dictionaries, glossaries, Internet information, parallel corpora in multiple languages, comparable corpora in multiple languages, and human-created translations. The generic training data may be related to any domain and may comprise millions of sentences. The specialized data is derived from parallel or comparable bilingual data relating to the domain associated with the domain-based translation engine 106. The specialized data and the generic training data may be merged according to the system and method described in U.S. patent application Ser. No. 11/223,823 filed Sep. 9, 2005 and entitled “Adapter for Allowing Both Online and Offline Training of a Text to Text System.”

The translation memory storage device 208 may comprise generic and/or data relating to the domain. The translation memory storage device 208 may further comprise specialized data received from the member 102A. In exemplary embodiments, the translation memory may be used by a statistical machine translation system as described in U.S. patent application Ser. No. 10/143,382 filed May 9, 2002 and entitled “Statistical Memory-Based Translation System.” While a hybrid statistical machine translation/translation memory translation engine is described herein, other data-driven machine translation techniques may be performed by the domain-based translation engine to generate a translation as is known in the art.

FIG. 3 is a block diagram of the customization engine 108 according to an embodiment. The customization engine is configured to generate a domain-based translation engine 106 based on specialized data. In some embodiments, the customization engine 108 may be combined with the domain-based translation engine 106.

A communications module 302 is configured to receive and transmit data via the network 112. The communications module 302 may receive specialized data from members 102A through 102N, domain-based translation engines 106, or other sources connected to the network 112. The communications module 302 may format and/or process the specialized data to generate domain parameters that can be processed by an adaptation module 308.

In exemplary embodiments, a specialized data storage device 304 may store specialized data comprising millions of words. The source of these words may be specialized data received from the members 102, data derived from other members, data derived from public sources, or any combination of sources. The specialized data storage device 304 may store specialized data as raw data, aligned words or segments, statistical machine translation parameters, a translation memory, or in any other format.

In exemplary embodiments, the adaptation module 308 is configured to generate a domain-based translation engine 106A based on the specialized data stored in the specialized data storage device 304, the translation memory storage device 208, and/or a set of stored generic parameters stored in a generic parameters storage device 310. In some embodiments, the adaptation module 308 may comprise an adapter as described in U.S. patent application Ser. No. 11/223,823 filed Sep. 9, 2005and entitled “Adapter for Allowing Both Online and Offline Training of a Text to Text System” for statistical machine translation. In other embodiments, the adaptation module 308 may generate a domain-based translation engine 106A using other techniques including, but not limited to, translation memory, heuristics-based, context-based, linguistics-based, or any hybrid translation technique.

The generic parameters stored in the generic parameters storage device 310 may be derived from a large bilingual corpus comprising approximately hundreds of millions of words according to one embodiment. In the depicted embodiment, the generic parameters stored in the generic parameters storage device 310 are shown as part of a statistical machine translation system. In other embodiments, however, the generic parameters may comprise a translation memory, a set of heuristics, linguistic-based and/or context-based data, or the like. The generic parameters may comprise any combination of the above.

FIG. 4 is a block diagram of the translation memory engine 110 according to an embodiment. The translation memory engine 110 is configured to generate a translation memory based on specialized data.

A communications module 402 is configured to receive and transmit data via the network 112. The communications module 302 may receive specialized data from members 102A through 102N, domain-based translation engines 106, or other sources connected to the network 112. The communications module 402 may format the specialized data.

In some embodiments, the translation memory engine 110 may comprise a translation memory module 404. The translation memory module 404 is configured to generate parallel data from a collection of documents. In exemplary embodiments, the documents may be stored in a variety of file formats and/or contain formatting.

The translation memory module 404 may find parallel or comparable documents in a collection according to the systems and methods described in U.S. patent application Ser. No. 11/635,248 filed Dec. 5, 2006 and entitled, “Systems and Methods for Identifying Parallel Documents and Sentence Fragments in Multilingual Document Collections,” which is incorporated herein by reference. Next, the translation memory module 404 may align the sentences of the parallel documents using prior art sentence alignment methods to generate a translation memory. The translation memories may be stored in a translation memory storage device 208. In some embodiments, the translation memory storage device 208 may be located at the member 102A.

FIG. 5 is a flowchart of process 500 for generating a domain-based translation engine 106A or a translation memory storage device 208 according to an embodiment of the present invention. The process 500 may be performed by the translation service system 104.

In step 502, specialized data is received by, for example, the translation service system 104. The received data may comprise specialized data received from a member, specialized data retrieved from public sources, or the like. The specialized data may be associated with a domain, a source language, and a target language. The specialized data may comprise parallel or comparable documents, an aligned bilingual corpus, a translation memory, a bilingual terminology list, a translation dictionary, a set of statistical machine translation parameters, or the like.

In some embodiments, the specialized data may be associated with the member 102A for the purpose of maintaining confidentiality of the data and/or managing credits to the member 102A for allowing the specialized data to be used by other domain-based translation engines. The member 102A may, for example, indicate that at least a portion of the specialized data requires a high level of confidentiality. This specialized data may then be used for translation memories and/or generating statistical machine parameters that only the member 102A may access. The member 102A may, alternatively or additionally, elect to share another portion of the specialized data. When this shared specialized data is used by the domain-based translation engine to translate an input string received from another member, the member 102A may receive a credit.

In step 504, a determination is made as to whether the member 102A requires the development of a domain-based engine and whether there is a sufficient amount of specialized data to generate a domain-based engine, such as the domain based translation engine 106A, by, for example, the adaptation module 308. To generate a domain-based translation engine, more than 50,000 words of parallel data may be required. The domain-based translation engine may be based on the data or a translation memory associated with a single member 102A. In some embodiments, the single member 102A may be associated with multiple sets of specialized data that may each be associated with a separate domain-based translation engine.

If there is insufficient data to generate a domain-based translation engine, a translation memory, such as the translation memory stored in the translation memory storage device 208, may be generated and/or updated based on the specialized data in step 506. The translation memory may be used along with merged parameters by a domain-based translation engine to translate input text strings as discussed, at least, in connection with FIG. 2. If there is sufficient data to generate a domain-based translation engine and the member 102A requires so, a domain-based translation engine is generated in step 508.

FIG. 6 is a flowchart of a process 600 for providing a translation service according to an embodiment of the present invention. The translation service may be free, subscription-based, usage fee-based, or any other fee-based scheme. In step 602, the translation memory may be generated based on specialized data and stored in the translation memory storage device 208. The translation memory engine 110 may generate the translation memory. Alternatively or additionally, in step 604, the domain-based translation engine may be generated. The domain-based translation engine may be generated according to the process 500 and may comprise the domain-based translation engine 106A. In some embodiments, the customization engine 108 may generate the domain-based translation engine. The domain-based translation engine may comprise, or have access to, the translation memory.

In step 606, an interface accessible via the Internet is provided. In step 608, a text string written in a source language is received. The text string may be of any length. In some embodiments, the text string is associated with a file format and/or comprises formatting that may be preserved when the text string is translated. In step 610, a selection indicating the domain-based translation engine and/or the translation memory is received. The selection may comprise a source language, a target language, and/or a domain. The selection may also comprise a sub-domain or member-specific domain.

A member-specific domain comprises a domain-based translation engine or translation memory generated using specialized data received from a specific member, referred to as an originating member. In exemplary embodiments, the member-specific domain may be accessed only by the originating member. In some embodiments, the originating member may identify other members 102 who are able to access the member-specific domain. In other embodiments, the member-specific domain may be open to any other member 102. In the embodiments where the member-specific domain is available to other members 102, the originating member may receive a credit if another member 102 selects the member-specific domain to translate an input text string. The credit may comprise points redeemable for additional translations, cash, or any other form of compensation.

In step 612, the text string is translated using the domain-based translation engine 106A. The domain-based translation engine 106A may use one or more techniques to translate the text string as discussed herein. In some embodiments, the translation service system 104 may indicate, through the use of annotations, highlighting, or other formatting, which technique is used. In some embodiments, the indication may represent a confidence level that the translation is accurate. This confidence level information may indicate a probability that the translation is correct. For example, a translated phrase within the text string that was translated using a translation memory is likely to be 100% correct while a translation based on the merged parameters is less likely to be correct. Thus, the translated text may be annotated to indicate the portions translated using the translation memory and the merged parameters, respectively. In other embodiments, the confidence level information may be calculated using other techniques known to those skilled in the art.

In step 614, the translated text string is transmitted to the member 102. The translated text string may comprise confidence level information, a timestamp, a domain-based translation engine identifier, or the like. The translated text string may be associated with a same or a different file format than that associated with the text string. In some embodiments, formatting within the text string may be included in the translated text string.

The above-described functions and components can be comprised of instructions that are stored on a storage medium. The instructions can be retrieved and executed by a processor. Some examples of instructions are software, program code, and firmware. Some examples of storage medium are memory devices, tape, disks, integrated circuits, and servers. The instructions are operational when executed by the processor to direct the processor to operate in accord with various embodiments. Those skilled in the art are familiar with instructions, processor(s), and storage medium.

While various embodiments have been described above, it should be understood that they have been presented by way of example only, and not limitation. The scope of the present disclosure is in no way limited to the languages used to describe exemplary embodiments. Thus, the breadth and scope of a preferred embodiment should not be limited by any of the above-described exemplary embodiments

Claims

1. A method for providing a translation service comprising: receiving a text string written in a source language from a member via a translation interface;receiving specialized data associated with: a domain from the member via the translation interface, andan indication of confidentiality;generating a translation memory using the received specialized data;generating a set of domain-specific parameters for statistical machine translation using the received specialized data;merging the generated set of domain-specific parameters with a generic set of statistical machine translation parameters;generating a domain-based translation engine based on the received specialized data and generic data, the domain-based translation engine associated with a source language, a target language, and the domain;training the domain-based translation engine using the translation memory;receiving a selection of the generated domain-based translation engine from a plurality of domain-based translation engines, the selection received from the member via the translation interface;translating the text string into the target language using, at least in part, the selected domain-based translation engine, the merged parameters and translation memory being used by the domain-based translation engine for translating the text string; andtransmitting the translated text string to the member via the translation interface over a network.
2. The method of claim 1, wherein the translation interface is accessible via the network, the translation interface configured to receive translation memory associated with the domain from another member.
3. The method of claim 1, further comprising sending the generated translation memory to the member for storage.
4. The method of claim 1, further comprising: translating a first portion of the text string using the translation memory;annotating the translation of the first portion of the text string with a first confidence level;translating a second portion of the text string using the merged parameters; andannotating the translation of the second portion of the text string with a second confidence level.
5. The method of claim 1, further comprising: determining if the specialized data includes a sufficient amount of data for generating a domain-based translation engine; andgenerating the domain-based translation engine based on the determination that the specialized data includes a sufficient amount of data and a requirement received from the member to generate the domain-based translation engine using the specialized data.
6. The method of claim 1, further comprising: translating a second text string received from a second member using, at least in part, specialized data received from the second member; andcrediting an account associated with the second member.
7. The method of claim 1, further comprising receiving a payment from the member based on a subscription.
8. The method of claim 1, further comprising receiving a payment from the member based on a usage fee.
9. The method of claim 1, further comprising providing to the member confidence level information based on the merged parameters and associated with the translated text string.
10. The method of claim 1, wherein translating the text string is performed using, at least in part, a data-driven machine translation technique.
11. A domain-based translation engine comprising: a communications module configured to receive specialized data and to receive a source language text string written in a source language and to receive a target language text string written in a target language, from a member via a network;a translation module configured to translate the source language text string into the target language and to translate the target language text string into the source language using, at least in part, data-driven machine translation and the specialized data, wherein the domain-based translation engine is generated based on received domain data; anda customization engine configured to determine whether an amount of the specialized data is sufficient to generate the domain-based translation engine and generate a language memory using the specialized data if the amount of the specialized data is not sufficient or to generate the domain-based translation engine if the amount of the specialized data is sufficient.
12. The domain-based translation engine of claim 11, wherein the translation module is communicatively coupled with a translation memory engine configured to generate translation memory used for training the domain-based translation engine and accessed by the domain-based translation engine to translate the input text string.
13. A computer readable non-transitory medium having embodied thereon a program, the program being executable by a processor for performing a method for providing a translation service, the method comprising: receiving a text string written in a source language from a member via a translation interface;receiving translation memory from the member, the translation memory associated with the source language, a target language, and a domain;receiving specialized data associated with the domain, the source language, and the target language, the specialized data including a set of domain-based statistical machine translation parameters;merging the domain-based statistical machine translation parameters and a set of generic statistical machine translation parameters;determining if the specialized data includes a sufficient amount of data for generating a domain-based translation engine;receiving instructions from the member to generate the domain-based translation engine using the translation memory;generating the domain-based translation engine based on the determination that the specialized data includes a sufficient amount of data and a requirement received from the member to generate the domain-based translation engine using the specialized data;training the generated domain-based translation engine using both the translation memory and the specialized data;receiving a selection of the domain-based translation engine from the member;translating the text string into the target language using, at least in part, the selected domain-based translation engine, the received translation memory and the merged translation parameters accessed by the domain-based translation engine for translating the text string; andtransmitting the translated text string to the member via the translation interface over an Internet.
14. The computer readable medium of claim 13, wherein the method further comprises: receiving specialized data associated with a domain from another member; andtraining the domain-based translation engine using the specialized data associated with the domain from another member and generic data.
15. The computer readable medium of claim 13, wherein the method further comprises translating at least a portion of the text string using the received translation memory and another portion of the text string using the merged parameters.
16. The computer readable medium of claim 13, wherein the method further comprises generating the domain-based translation engine using a customization engine based on the translation memory received from the member.
17. The computer readable medium of claim 13, wherein the method further comprises: translating a second text string received from a second member from the target language to the source language using, at least in part, the domain-based translation engine; andcrediting an account associated with the member.
18. The computer readable medium of claim 13, wherein the method further comprises providing confidence level information associated with the parameters used for translating the text string.
19. The computer readable medium of claim 13, wherein specialized data is associated with an indication of confidentiality.
20. A method comprising: receiving a plurality of documents from a member, a first document of the plurality of documents written in a first source language and a second document of the plurality of documents written in a second source language;receiving instructions from the member including instructions to use a first domain-based translation engine for translating the first document and instructions to use a second domain-based translation engine for translating the second document;receiving a set of domain-based statistical machine translation parameters;merging the domain-based statistical machine translation parameters and a set of generic statistical machine translation parameters;generating a first translation memory based on the first domain-based translation engine;sending the first translation memory to the member for storage;translating a first portion of the first document using the first translation memory based on the first domain-based translation engine and generic data;annotating the translation of the first portion of the first document with a first confidence level;translating a second portion of the first document using the merged parameters;annotating the translation of the second portion of the first document with a second confidence level; andgenerating a translation of the second document based on the second domain-based translation engine and generic data.
21. The method of claim 20, further comprising generating the second domain-based translation engine based on a second translation memory and the plurality of documents.
22. The method of claim 21, further comprising translating a text string received from another member using the second domain-based translation engine.
23. The method of claim 20, wherein the first document is associated with a first format and the second document is associated with a second format.

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	Number	Date	Country
	20080249760 A1	Oct 2008	US

Customizable machine translation service

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