Patent Application
20150106702
This disclosure relates to the technical field of computer input.
The continued proliferation of computing devices has led to an increase in the availability of applications and other content used on these devices. For instance, users employ a variety of applications, such as games, digital media players, browsers, and the like, on an assortment of computing devices. As the number of computing devices and applications used on these devices continues to increase, users are ever more interested in enhancing their experiences while using these computing devices and applications.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some implementations provide techniques and arrangements for cross lingual candidate suggestion. For example, some implementations display a user interface of a host application including a text entry area. An input method editor (IME) receives one or more characters as input. In response, one or more completion candidates are displayed, at least one of the completion candidates being a cross lingual completion candidate in a language different from the one or more characters.
The Detailed Description is described with reference to the accompanying figures. The use of the same reference numbers in different figures indicates similar or identical items.
This disclosure includes techniques and arrangements for cross lingual input methods, and in some implementations, for a cross lingual input method editor (IME) that provides completion candidates to a user for insertion into a computer application. In some implementations, the cross lingual IME provides completion candidates based, at least in part, on contextual information related to the user input.
In some implementations that involve an IME, the system assists a user in entering text in a first language by allowing the user to enter a corresponding text in a second language and then providing suggested candidates in the first language for insertion into a computer application. Consider the following scenario. A user is entering text into an IME in Spanish, but the user's first language is English. In such a scenario, the user may have difficulty thinking of the appropriate Spanish term, but know the appropriate English term. Some implementations provide assistance to the user by enabling the user to input the appropriate English term to the IME, then present the user with a list of suggested Spanish candidate terms for selection by the user and insertion into a host program by the IME.
Other implementations may not involve an IME, but rather perform cross lingual assisted functionality in other programs such as a spell checking function in a word processor program, an autocomplete function of applications such as a text messaging program of a mobile computing device, a character/word recognition functionality of handwriting recognition applications, and word recognition functionality of voice recognition/dictation applications. This list is not meant to be exhaustive and example implementations are merely examples which are not to be taken as limiting. Thus, it should be understood that, though this disclosure may, for ease of understanding, describe the system and method in the context of an IME, the system and method described herein are not limited to such uses and may be used in many other situations.
The cross lingual assistance functionality described herein may be implemented at various levels in the software and hardware of computing systems. Such levels include the Operating System (OS) level, such as in the OS with or without application support, the application level, either separate from the OS (i.e. stand-alone) or as a plug-in to the OS or a plug-in to another application and so forth. Further, the cross lingual assistance functionality may be implemented universally for all text entry areas in all applications, such as in OS only implementations, or the functionality may only be active in select text entry areas, either in specific programs (e.g. a OS level IME), classes of programs (e.g. dedicated IMEs of individual programs), specified text entry areas, classes of text entry areas, and so forth. Moreover, some implementations may allow a user to set various parameters of the cross lingual assistance functionality such as, the class of programs or text entry areas that implement the functionality, the languages and writing systems to be used for the functionality and so forth.
As stated above, an input method editor (IME) is a computer application that assists a user to input text to a computing device. An IME may provide several completion candidates based on inputs received from the user. In some implementations of a cross lingual IME described herein, the input text and the provided candidate texts may be in the same language and/or writing system or different languages and/or writing systems or some combination thereof.
For example, the user may input one or more initial Latin characters of an English word or phrase and an IME, based on the initial characters, provides one or more complete English words or phrases from which the user is able to select a proper one. Such a function is referred to as an autocomplete function or may be referred to as a same language completion candidate suggestion. In some implementations, the autocomplete functionality may be implemented as a client-side binary-search-based data structure.
In another example, an IME may also assist the user to input non-Latin characters such as East Asian characters (e.g. Hanzi) through transliteration. This function of an IME may allow a user to input non-Latin characters in popular operating systems whose keyboards usually only support inputting Latin characters. For example, the user may input Latin characters through a keyboard to form a phonetic spelling of a Chinese Hanzi character. The IME returns one or more Chinese characters based on the spelling to the user to select a proper one. One such phonetic writing system for Chinese is Pinyin, which can be properly described as a transliteration of Chinese into Latin characters (also referred to as a Romanization of Chinese).
In a further example, an IME combines the transliteration function just described with a translational function to assist a user writing in a first language when the user is unable to recall the appropriate term in that first language but can recall the corresponding word in the non-Latin character writing system of a second language. This is similar to the English and Spanish example provided. However, in this case, using Chinese as an example, the IME performs recognition of the Pinyin term, determines candidate transliterations of the Pinyin term into Chinese Hanzi characters, determines English translations of the candidate Hanzi terms, and then provides user with the candidate Hanzi terms and their corresponding English equivalents. The user then selects a chosen candidate term. The English equivalent completion candidate selected by the user may then be inserted into various other computer applications, such as a chatting application, a document editing application, a gaming application, etc.
In some implementations, a listing of completion candidates could include both same language completion candidate and cross language completion candidates.
In discussions involving two languages, the discussion herein may use specific languages for ease of comprehension. For example, several figures use English and Chinese as examples while another uses English and Spanish. In such discussions, the examples may be generalized to any first language and second language. Specifically, English may be generalized in these discussions to any first language and Chinese and Spanish may be generalized to refer to any second language.
In the example shown in
In some implementations, such as the one shown in
For ease of discussion and comprehension,
At block 302, the computing device 102 displays the host application 106 and input method editor (IME) 108 on the touchscreen display 104.
At block 304, the computing device 102 receives a character input. As discussed above, implementations of the techniques and arrangements disclosed herein may utilize a wide variety of input methods and devices. However, for brevity, the discussion of
At block 306, the IME 108 analyzes the received character input and, based thereon, determines suggested completion candidates in a first language and a second language, English and Chinese respectively. It should be noted that the IME 108 may take other information into consideration in its determination. Some examples of other information will be discussed below. The process flow then continues to block 308.
At block 308, IME 108 displays any suggested completion candidates in the candidates window 114. The flow then proceeds to block 310.
At block 310, the IME 108 awaits one of three events. First, if the IME 108 receives an entry of one or more additional characters 312 (other than a character input selecting a candidate term to be inserted), the flow returns to block 306 and a new determination of suggested completion candidates is performed.
Second, if at block 310, the IME 108 receives a selection of a suggested completion candidate 314 for insertion into the host application 106, the flow moves to block 316. At block 316, the selected completion candidate is inserted into the text entry area 110 of the host application 106 in a manner that may be similar to that discussed above regarding the insertion of the word “hello” into the host application 106 and shown in
Third, if at block 310, the IME 108 receives an input specifying the completion of a word without the use of a completion candidate 320 (e.g., an instruction to insert a space or the like to indicating a shift to a new word), the flow moves to block 322. At block 322, the contents of the composition window 112 is inserted into the text entry area 110 of the host application 106. As an example, such a situation may occur when the user wishes to insert a non-English term into the text. The flow then moves to block 318.
At block 318, either a suggested completion candidate or the contents of the composition window 112 has been inserted into the text entry area 110 of the host application 106 by the IME 108. The IME 108 then clears the composition window 112 and the candidates window 114, such that the IME is prepared for subsequent input. Though not shown, the process flow 300 could then move back to block 304 upon receiving a further character input.
As mentioned above, the IME 108 may take into account information in addition to the received character input in determining suggested completion candidates. In some implementations, this additional information includes contextual information. Two example types of contextual information that may be used are N-grams and scenario information. An example of an N-gram is a sequence of N words to the left of the cursor and M words to the right of the cursor. An example of scenario information is information that includes items such as the process name, input scope (field type/name), version of the application, and version of the operating system. In some implementations, the received character input (i.e. the contents of the composition window 112) may be used to generate any number of completion candidates that could be displayed in the candidates window 114. The contextual information, such as N-grams and scenario information may be used in some implementations to rank the generated completion candidates for display to the user. In cases in which the number of completion candidates generated is larger than the number that can be displayed in the candidates window, the additional information may be used to select which completion candidates will be displayed.
In some implementations, N-grams may be useful at the content level of the document, and scenario information may provide information about the document itself and environmental context.
With N-grams, the system may detect distinct “trigger words” like “said” that co-occur highly with a translated Chinese equivalent, as seen statistically, for example, on the web, with words like “hello.” Consequently, in implementations that include N-gram information, a candidate term may appear higher on the candidate ranking list if the nearby text of the N-gram contains a trigger term associated with that candidate. The discovery of trigger words and their corresponding collocated terms is a computational linguistic method called “collocation extraction.” Generalizing this, some implementations may build a language model, which is then employed to probabilistically affect the ranking of candidates based on context. Implementations may also apply the N-gram analysis in a cross lingual context such that the context is analyzed between terms written in a different languages, and further, in non-Latin writing systems of such languages, the analysis is performed between a transliteration of a language with term of another language.
Scenario information may be used as another feature in the ranking. In some implementations, the IME 108 uses the input scope and application name to provide a signal implying different styles of writing. For example, the writing style which one may employ when conversing with their manager in an email within Microsoft Outlook® might be different from the writing style one uses to communicates with a family member on Windows Live Messenger, Hotmail or Gmail. As an example, the scenario information might include the information that the input scope is an email message body and the application name is Outlook.
An example of this analysis can be seen in
The first variation can be seen in the candidates window 402 of the IME 400 in item 404. Specifically, the IME 400 has provided completion candidates that are direct English-to-English completions in item 404, but nonetheless shows the Hanzi characters of the corresponding Chinese words next to the suggested completion candidates. This illustrates that the display of the Hanzi characters in the candidates window 402 may be, but is not required to be limited to cross lingual candidate suggestions such as those discussed with regard to
The second variation is that IME 400 of the implementation shown in
At item 404, a user has entered “When we met I said, nih” to the composition window of the input method editor 108. The phrase “When we met I said,” has been inserted into the host application in a manner such as that shown in
At 404, the user has now input “niha” to the composition window of the input method editor 400. At this point, the number of characters is greater than four (the example discussed above) and the number of English language words having this beginning is limited to one proper Noun name of a city “Nihau.” Thus, in item 404, the IME 400 determines that cross lingual candidate suggestion should be performed. As a result of the cross lingual candidate suggestion analysis, the IME 400 determines that “nihao” is a possible Pinyin completion of “niha.” Next, the IME 400 performs the context analysis discussed above, including the collocation determination. From this, it is determined that, of the Hanzi terms corresponding to the Pinyin word “nihao,” the term that translates into English as “hello” or “how are you?” is the highest ranked. It then determines that the English equivalent “hello” has a higher statistical probability of being chosen based at least in part on the collocation of “said” with “hello.” In the example implementation shown in
For brevity, it should be understood that this ranking process, or one similar thereto, may be applied to the completion candidates in any given implementation to determine which candidate terms will be presented in the candidates window and the order which completion candidates will be presented. Thus, unless stated otherwise, it should be assumed that similar processes described in this specification may also implement such a ranking/selection technique, but this is not to be taken as a limitation.
Following the state illustrated at 406, should the user finish inputting the term “nihao” into the composition window 402, the IME 400 will mirror the appearance of IME 108 in
At item 506, the IME 500 receives the input characters “wom,” processes the entered characters and, returns the English words, “women,” “woman,” and “womenswear.” Unlike IME 400, which included the Hanzi equivalent of any English term shown in the candidates window 402, IME 500 does not show Hanzi equivalents of same language completion candidates (i.e. direct English to English candidates). For example, at 506, the English terms “women,” “woman” and “womenswear” are not accompanied by their Hanzi equivalents as they are same language completion candidates proposed based on an English use of the root “wom.” The lack of Hanzi equivalents for same language completion candidates may be due to a variety of factors such as the IME 500 being designed to not include equivalents for same language completion candidates or the IME 500 may have a user setting that allows the display of the Hanzi equivalents for same language completion candidates to be enabled or disabled.
Further, in the implementation shown in
At item 508, the IME 500 receives input of the character, “e,” processes the text in the composition window 112 (i.e. “wome”), and returns two English words, “women” and “woman.” As mentioned to above, in the example implementation illustrated in
At item 510, the IME 500 receives input of the character “n,” processes the text in the composition window 112 (i.e. “women”), and returns two English words, “women” and “woman.” During the processing of the term “women,” the IME 500 also determines that “women” is a transliteration of at least one Chinese word. Accordingly, the IME 500 obtains information regarding cross lingual completion candidates for the pinyin-Chinese term “women” for possible display in the candidates window 502. In some implementations, the IME 500 determines that the English terms, “we,” “our,” and “ourselves” are each possible translations of the pinyin transliteration “women.” The IME 500 performs ranking/selection on these terms as well as the English completion suggestions “women” and “womenswear” to obtain and present the list shown in candidates window 502 at item 510. In the non-limiting implementation shown at 510, the term “women” is ranked at the top of the list due to its common collocation with the words/phrase “men and” as part of the phrase “men and women.” Womenswear, while not having a contextual “score” as high as women, is found to have a higher score than “we” and “our.” The rankings continue down the list. This results in the lowest ranked completion candidate, “ourselves,” not being shown in the candidates window 502 due to it not fitting within the available space.
Following the state illustrated at 510, the user may continue by selecting one of the candidates for insertion, inputting an appropriate command to insert the contents of the composition window without regard to any of the suggested completion candidates, or by entering a further character.
The client device 602 includes a host application 608 and a client side input method editor (IME) application 610. The client side IME application 610 includes a user interface 612, a context component 614, an analysis component 616, and a presentation component.
The host application 608 is similar to the host application 106 discussed above with regard to
Some modules of the client side IME application 610 may be implemented as separate systems and their processing results can be used by the IME 610. For the sake of convenient description, the above IME is functionally divided into various modules which are separately described. When implementing the disclosed system, the functions of various modules may be implemented in one or more instances of software and/or hardware.
The one or more server devices 604 may each include a server side input method editor application 620. The server side IME application 620 includes a statistic analysis and storage component 622, an analysis component 624, and a communication component 626.
The statistic analysis and storage component 622 creates and maintains statistical information, index tables of transliterations and translations, and other pieces of information to be used by the one or more server devices 604 to answer queries from the client device 602.
The analysis component 624 uses the received characters and context information in queries from client devices, as well as information stored by the statistic analysis and storage component 622 to determine cross lingual completion candidates based on a second language as well as, depending on the particular implementation, completion candidates in the first language. The analysis component 624 may also select the terms to be presented as completion candidates and the order for their presentation using a ranking technique, such as the technique described above with respect to
The communication component 626 conducts communication between the components of the one or more server devices 604 with other devices, such as the client device 602, across network 606.
There may be other configurations of an IME system in a client-server architecture. In another example, the analysis component 616 may be located in the one or more server device(s) instead of the client device 110. In yet another example, the analysis component 624 of the one or more server devices 604 may be incorporated into the client device 602.
At block 302, the user interface 612 of the client side input method editor application 610 causes a graphical user interface (GUI) of the client side input method editor (IME) 610 to be displayed, for example, over the host application 608 on a touchscreen display such as touch screen display 104. At block 304, user interface 612 of the client device 602 receives a character input.
At block 702, the context component 614 collects data relating to the context of the received character input. The analysis component 616 analyzes received character input and determines any suggested completion candidates in a first language based on received input. The flow then proceeds to block 704.
At block 704, the analysis component 616 determines whether to query the one or more server devices 604 regarding suggested completion candidates based on a second language. If the analysis component 616 determines that the server should not be queried, the process flow then continues to block 308. If the analysis component 616 determines that the server should be queried, the process flow then continues to block 706.
At block 706, the communication component 618 send an inquiry to the one or more servers 604. The inquiry includes information such as the received input characters, the contextual information, etc. Depending on the particular implementation, information in addition to suggested completion candidates based on a second language may be queried as well. For example, the inquiry could request a selection of the suggested completion candidates to be presented and the order for presentation. The flow then proceeds to block 708.
At block 708, the communication component 618 receives a response to the inquiry from the one or more servers 604. The flow then proceeds to block 308.
The operation of blocks 308-318 shown in
Once the flow reaches block 318, either a suggested completion candidate or the contents of the composition window 112 has been inserted into the host application 608 by the client side IME application 610. The client side IME application 610 then clears its composition window and candidates window, such that the client side IME is prepared for subsequent input. Though not shown, the process flow 700 could then move back to block 302 of
At block 802, the one or more server devices 604 are initialized. Because, in the example implementation shown in
In some implementations, this allows the server devices 604 to utilize large quantities of memory. These indices are loaded into memory at the initialization of a particular server to allow for rapid completion of queries. The indices and tables may be generated from statistical information gathered from logs of previous cross lingual completion requests so as to pre-rank them using probabilities that map roughly to the popularity of terms queried in the past. In some implementations, a decoder for traversing these tables may take into account the aforementioned context parameters and leverages supervised learning algorithms for producing results that get better over time. That is, the user selection of a particular candidate from a group of candidates is “learned” at a global scale and, by leveraging log data, eventually offers results that may better match users' needs in particular contexts.
At block 804, the server devices 604 receive a query from the client side IME application 610 that includes one or more character corresponding to the contents of a composition window of the client side IME application 610, as well as contextual information such as scenario and n-gram information. The flow then proceeds to block 806.
At block 806, the server devices 604 determine completion candidates based on a language (i.e. the second language) different from that of the one or more characters (i.e. the first language), as well as, depending on the particular implementation, suggested completion candidates in the language of the one or more characters (i.e. the first language). The flow then proceeds to block 808.
At 808, the analysis component 624 selects one or more of the determined completion candidates to be returned to the client device 602 as completion candidates for display in the client side IME application 610 and a ranking order for their presentation using a ranking technique as the technique described above with respect to
At 810, the communication component 626 sends the generated and ranked completion candidates, (if any) to the client device 602, across network 606. Though any number of communication formats could be used for the server response, in some implementations, the server response format is XML. An example XML response is shown below in Table 1 that could be used to return the contents of the candidates window 502 as shown in item 510 of
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</h>
</h>
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While several examples have been illustrated herein for discussion purposes, numerous other configurations may be used and thus implementations herein are not limited to any particular configuration or arrangement. For example, as previously mentioned, the functionality provided by the disclosed techniques and arrangements are not limited to input method editors.
The discussion herein refers to data being sent and received by particular components or modules system. This should not be taken as a limitation as such communication need not be direct and the particular components or module need not necessarily be a single functional unit. For example, the statistic analysis and storage component 622 and analysis component 628 are discussed as separate logical components of the system which carry out separate functions and communicate with each other. This is not to be taken as limiting implementations to only those in which the components directly send and receive data from one another. The signals could instead be relayed by a separate component upon receipt of the data. Further, the components may be combined or the functionality may be separated amongst components in various manners not limited to those discussed above. Other variations in the logical and practical structure and framework of various implementations would be apparent to one of ordinary skill in the art in view of the disclosure provided herein.
The processes described herein are only examples provided for discussion purposes. Numerous other variations will be apparent to those of skill in the art in light of the disclosure herein. Further, while the disclosure herein sets forth several examples of suitable frameworks, architectures and environments for executing the techniques and processes herein, implementations herein are not limited to the particular examples shown and discussed. The processes illustrated herein are shown as a collection of operations in a logical flow graph, which represents a sequence of operations, some or all of which can be implemented in hardware, software or a combination thereof. In the context of software, the blocks represent computer-executable instructions stored on one or more computer-readable media that, when executed by one or more processors, perform the recited operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures and the like that perform particular functions or implement particular abstract data types. The order in which the operations are described is not intended to be construed as a limitation. Any number of the described blocks can be combined in any order and/or in parallel to implement the process, and not all of the blocks need be executed.
The computing device 1100 may include at least one processor 1102, a memory 1104, communication interfaces 1106, a display device 1108 (e.g. a touchscreen display), other input/output (I/O) devices 1110 (e.g. a touchscreen display or a mouse and keyboard), and one or more mass storage devices 1112, able to communicate with each other, such as via a system bus 1114 or other suitable connection.
The processor 1102 may be a single processing unit or a number of processing units, all of which may include single or multiple computing units or multiple cores. The processor 1102 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor 1102 can be configured to fetch and execute computer-readable instructions stored in the memory 1104, mass storage devices 1112, or other computer-readable media.
Memory 1104 and mass storage devices 1112 are examples of computer storage media for storing instructions which are executed by the processor 1102 to perform the various functions described above. For example, memory 1104 may generally include both volatile memory and non-volatile memory (e.g., RAM, ROM, or the like). Further, mass storage devices 1112 may generally include hard disk drives, solid-state drives, removable media, including external and removable drives, memory cards, flash memory, floppy disks, optical disks (e.g., CD, DVD), a storage array, a network attached storage, a storage area network, or the like. Both memory 1104 and mass storage devices 1112 may be collectively referred to as memory or computer storage media herein, and may be capable of storing computer-readable, processor-executable program instructions as computer program code that can be executed by the processor 1102 as a particular machine configured for carrying out the operations and functions described in the implementations herein.
The computing device 1100 may also include one or more communication interfaces 1106 for exchanging data with other devices, such as via a network, direct connection, or the like, as discussed above. The communication interfaces 1106 can facilitate communications within a wide variety of networks and protocol types, including wired networks (e.g., LAN, cable, etc.) and wireless networks (e.g., WLAN, cellular, satellite, etc.), the Internet and the like. Communication interfaces 1106 can also provide communication with external storage (not shown), such as in a storage array, network attached storage, storage area network, or the like.
A display device 1108, such as touchscreen display 104 or other display device, may be included in some implementations. Other I/O devices 1110 may be devices that receive various inputs from a user and provide various outputs to the user, and may include a touchscreen, such as touchscreen display 104, a keyboard, a remote controller, a mouse, a printer, audio input/output devices, and so forth.
Memory 1104 may include modules and components for the computing device 1100 according to the implementations discussed herein. In the illustrated example, memory 1104 includes the client side IME application 610 and the host application 608 as described above with regard to
The example systems and computing devices described herein are merely examples suitable for some implementations and are not intended to suggest any limitation as to the scope of use or functionality of the environments, architectures and frameworks that can implement the processes, components and features described herein. Thus, implementations herein are operational with numerous environments or architectures, and may be implemented in general purpose and special-purpose computing systems, or other devices having processing capability. Generally, any of the functions described with reference to the figures can be implemented using software, hardware (e.g., fixed logic circuitry) or a combination of these implementations. The term “module,” “mechanism” or “component” as used herein generally represents software, hardware, or a combination of software and hardware that can be configured to implement prescribed functions. For instance, in the case of a software implementation, the term “module,” “mechanism” or “component” can represent program code (and/or declarative-type instructions) that performs specified tasks or operations when executed on a processing device or devices (e.g., CPUs or processors). The program code can be stored in one or more computer-readable memory devices or other computer storage devices. Thus, the processes, components and modules described herein may be implemented by a computer program product.
Although illustrated in
Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information for access by a computing device.
In contrast, communication media may embody computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave, or other transmission mechanism. As defined herein, computer storage media does not include communication media.
Furthermore, this disclosure provides various example implementations, as described and as illustrated in the drawings. However, this disclosure is not limited to the implementations described and illustrated herein, but can extend to other implementations, as would be known or as would become known to those skilled in the art. Reference in the specification to “one implementation,” “this implementation,” “these implementations” or “some implementations” means that a particular feature, structure, or characteristic described is included in at least one implementation, and the appearances of these phrases in various places in the specification are not necessarily all referring to the same implementation.
Although the subject matter has been described in language specific to structural features and/or methodological acts, the subject matter defined in the appended claims is not limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. This disclosure is intended to cover any and all adaptations or variations of the disclosed implementations, and the following claims should not be construed to be limited to the specific implementations disclosed in the specification. Instead, the scope of this document is to be determined entirely by the following claims, along with the full range of equivalents to which such claims are entitled.
This application is a 35 U.S.C. 371 National Stage application of International Application No. PCT/CN2012/077896, filed Jun. 29, 2012, the entire contents of which are incorporated herein by reference.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/CN12/77896 | 6/29/2012 | WO | 00 | 9/14/2012 |
