Description:TECHNICAL FIELD
[0001] The present disclosure relates generally to processing of a multi-lingual query. In particular, the present disclosure relates to processing of a multi-lingual query, where the query is provided in a single script.

BACKGROUND
[0002] The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0003] E-commerce environments generally have a database of customers who use their services. In order to improve market penetration, there is a need to offer services in a plurality of languages in order to entice different linguistic groups of people. However, the e-commerce environment generally operates on one primary language, and any queries received by the environment in other languages are translated into the primary language. In some cases, queries may be received in other languages in scripts that are normally associated with the primary language.
[0004] There is, therefore, a requirement in the art for a means to accurately process a multi-script, multi-lingual query from a user.

SUMMARY
[0005] An object of the present invention is to provide a method and a system for processing a multi-script, multi-lingual query.
[0006] Another object of the present invention is to provide a method and system that does not require substantially additional memory for processing a multi-script, multi-lingual query.
[0007] Another object of the present invention is to provide a method and system that can be trained to improve accuracy of processing a multi-script, multi-lingual query.
[0008] In a first aspect, the present disclosure provides a method for processing a multi-script, multi-lingual query. The method includes receiving, by a computing device, an input query from a user device. The input query includes a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages. The input query includes a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the method includes converting, by the computing device, scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the method further includes translating, by the computing device, the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language. The method further includes generating, by the computing device, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language. The method further includes analyzing, by the computing device, the translated input query to determine a target token.
[0009] In a second aspect, the present disclosure provides a system for processing a multi-script, multi-lingual query. The system includes a computing device including a processor communicably coupled with a memory, the memory storing instructions, which when executed by the processor, causes the computing device to be configured to receive an input query from a user device. The input query includes a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages. The input query includes a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the computing device is configured to convert scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the computing device is further configured to translate the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language. The computing device is further configured to generate, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language. The computing device is further configured to analyze the translated input query to determine a target token.

BRIEF DESCRIPTION OF DRAWINGS
[0010] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry/subcomponents of each component. It will be appreciated by those skilled in the art that invention of such drawings includes the invention of electrical components, electronic components or circuitry commonly used to implement such components.
[0011] FIG. 1 illustrates a schematic block diagram of a network architecture for implementing a system for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure;
[0012] FIG. 2 illustrates a schematic block diagram of the system for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure;
[0013] FIG. 3A illustrates a schematic flow diagram for a method to generate training data, according to an embodiment of the present disclosure;
[0014] FIG. 3B illustrates a schematic flow diagram for a method for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure;
[0015] FIG. 4 illustrates an exemplary table demonstrating the method to generate a translated query from an input query; and
[0016] FIG. 5 illustrates a hardware platform for implementation of the disclosed system, according to an example embodiment of the present disclosure.

DETAILED DESCRIPTION
[0017] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0018] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0019] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0020] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0021] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0022] As used herein, "connect", "configure", "couple" and its cognate terms, such as "connects", "connected", "configured" and "coupled" may include a physical connection (such as a wired/wireless connection), a logical connection (such as through logical gates of semiconducting device), other suitable connections, or a combination of such connections, as may be obvious to a skilled person.
[0023] As used herein, "send", "transfer", "transmit", and their cognate terms like "sending", "sent", "transferring", "transmitting", "transferred", "transmitted", etc. include sending or transporting data or information from one unit or component to another unit or component, wherein the content may or may not be modified before or after sending, transferring, transmitting.
[0024] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0025] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
[0026] In a first aspect, the present disclosure provides a method for processing a multi-script, multi-lingual query. The method includes receiving, by a computing device, an input query from a user device. The input query includes a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages. The input query includes a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the method includes converting, by the computing device, scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the method further includes translating, by the computing device, the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language. The method further includes generating, by the computing device, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language. The method further includes analyzing, by the computing device, the translated input query to determine a target token.
[0027] In a second aspect, the present disclosure provides a system for processing a multi-script, multi-lingual query. The system includes a computing device including a processor communicably coupled with a memory, the memory storing instructions, which when executed by the processor, causes the computing device to be configured to receive an input query from a user device. The input query includes a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages. The input query includes a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the computing device is configured to convert scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. For the one or more sets of words in the respective one or more languages different from the primary language, the computing device is further configured to translate the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language. The computing device is further configured to generate, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language. The computing device is further configured to analyze the translated input query to determine a target token.
[0028] FIG. 1 illustrates a schematic block diagram of a network architecture 100 for implementing a system 200 for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure. The network architecture 100 may include the system 200, a server 102, one or more user devices 104-1, 104-2, 104-3, and a database 106. The server 102, the user devices 104 and the database 106 may be communicably coupled to the server 102 via a communication network 108. The system 200 may be implemented on the server 102. The server 102 may include, without limitations, a stand-alone server, a remote server, cloud computing server, a dedicated server, a rack server, a server blade, a server rack, a bank of servers, a server farm, hardware supporting a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof, and the like. The communication network 108 may be a wired communication network or a wireless communication network. The wireless communication network may be any wireless communication network capable of transferring data between entities of that network such as, without limitations, a carrier network including circuit switched network, a public switched network, a Content Delivery Network (CDN) network, a Long-Term Evolution (LTE) network, a Global System for Mobile Communications (GSM) network and a Universal Mobile Telecommunications System (UMTS) network, an Internet, intranets, local area networks, wide area networks, mobile communication networks, combinations thereof, and the like.
[0029] The system 200 may be implemented by way of a single device or a combination of multiple devices that may be communicably coupled or networked together. For instance, the system 200 may be implemented by way of standalone device such as the server 102, and the like, and may be communicably coupled to the user device 104. In another instance, the system 200 may be implemented in the user device 104. The user device 104 may be any electrical, electronic, electromechanical, and computing device. The user device 104 may include, without limitations, a mobile device, a smart phone, a Personal Digital Assistant (PDA), a tablet computer, a phablet computer, a wearable device, a Virtual Reality/Augment Reality (VR/AR) device, a laptop, a desktop, and the like.
[0030] The system 200 may be implemented in hardware or a suitable combination of hardware and software. Further, the system 200 may include a computing device including a processor, and a memory.
[0031] Further, the network architecture 100 may also include other units such as a display unit, an input unit, an output unit and the like; however, the same are not shown in the FIG. 1, for the purpose of clarity. Also, in FIG. 1 only few units are shown; however, the network architecture 100 may include multiple such units or the network architecture 100 may include any such numbers of the units, obvious to a person skilled in the art or as required to implement the features of the present disclosure. The system 200 may be a hardware device including the processor executing machine-readable program instructions for processing a multi-lingual query. Execution of the machine-readable program instructions by the processor may enable the proposed system 200 to process a multi-lingual query. The “hardware” may include a combination of discrete components, an integrated circuit, an application-specific integrated circuit, a field programmable gate array, a digital signal processor, or other suitable hardware. The “software” may include one or more objects, agents, threads, lines of code, subroutines, separate software applications, two or more lines of code or other suitable software structures operating in one or more software applications or on one or more processors. The processor may include, without limitations, microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, any devices that manipulate data or signals based on operational instructions, and the like. Among other capabilities, the processor may fetch and execute computer-readable instructions in the memory communicably coupled with it, for performing tasks such as data processing, input/output processing, feature extraction, and/or any other functions. Any reference to a task in the present disclosure may refer to an operation being or that may be performed on data.
[0032] FIG. 2 illustrates a schematic block diagram of the system 200 for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure. The system 200 includes a computing device 202. The computing device 202 includes a processor 204 communicably coupled with a memory 206. The memory 206 stores instructions executable by the processor 204 to enable the system 200 to process a multi-lingual query. The memory 206 includes various engines that may be executed by the processor 204 to enable the system 200 to process a multi-lingual query. The memory 206 includes a query script conversion engine 208, a query translation engine 210, a search engine 212, and a learning engine 214.
[0033] In some embodiments, the computing device 202 is communicably coupled to the database 106. The database 106 may be configured to store data. In some embodiments, the data may be stored in the form of various data structures. Additionally, the data can be organized using data models, such as relational or hierarchical data models. The data may further include temporary data and temporary files, generated by the computing device 202 while performing the various functions of the system 200.
[0034] Referring now to FIGs. 1 and 2, the query script conversion engine 208 is configured to receive an input query from a user device (e.g., the user device 104-2). The input query may include a plurality of sets of words. Each of the plurality of sets of words may correspond to a language from a plurality of languages. The input query may include a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language is in a first script associated with the primary language, and the one or more sets of words in the respective one or more languages different from the primary language are in respective one or more scripts associated with the respective one or more languages different from the primary language. For example, the primary language may be English, and the one or more languages may include languages other than English, which have non-roman scripts, such as, without limitations, Kannada, Telugu, Hindi, Tamil, Korean, Japanese, etc. However, the one or more sets of words in the one or more languages may be input in the script of the primary language.
[0035] For the one or more sets of words in the respective one or more languages different from the primary language, the query script conversion engine 208 is configured to convert scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language.
[0036] For the one or more sets of words in the respective one or more languages different from the primary language, the query translation engine 210 is configured to translate the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language.
[0037] In some embodiments, to translate the one or more sets of words in the respective one or more scripts different from the first script, the query translation engine 210 is further configured to transliterate the one or more sets of words in the respective one or more scripts different from the first script from the respective one or more languages different from the primary language to the primary language.
[0038] The query translation engine 210 is further configured to generate, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language.
[0039] The search engine 212 is configured to analyze the translated input query to determine a target token. In some embodiments, to analyze the translated input query, the search engine 212 is further configured to compare the translated input query with a dataset stored in the database 106 and map the translated input query with the dataset to determine the target token.
[0040] The search engine 212 is configured to execute a search of the database 106, based on the determined target token to generate a result set corresponding with the input query. The search result engine 212 is further configured to transmit the generated result set as an output.
[0041] The learning engine 214 is configured to generate training data. To generate training data, the learning engine 214 is configured to receive a plurality of input queries. Each of the plurality of input queries includes one or more sets of words in one or more languages different from the primary language. The one or more sets of words in each of the plurality of input queries are in the first script associated with the primary language. The learning engine 214 is further configured to convert scripts of the one or more sets of words of each of the plurality of input queries from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. The learning engine 214 is further configured to map each of the converted one or more sets of words of each of the plurality of input queries with the corresponding one or more sets of words of each of the plurality of input queries.
[0042] In some embodiments, the learning engine 214 is further configured to receive the plurality of input queries. At least one set of words from the one or more sets of words of each of the plurality of input queries has a spelling error. The learning engine 214 is further configured to receive corrected words corresponding to the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error. The learning engine 214 is further configured to map the corrected words with the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error.
[0043] FIG. 3A illustrates a schematic flow diagram for a method 300 to generate training data, according to an embodiment of the present disclosure. At step 302, the method 300 includes receiving, by the computing device 202, a plurality of input queries. Each of the plurality of input queries includes one or more sets of words in one or more languages different from the primary language. The one or more sets of words in each of the plurality of input queries are in the first script associated with the primary language. At step 304, the method 300 further includes converting, by the computing device 202, scripts of the one or more sets of words of each of the plurality of input queries from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. At step 306, the method 300 further includes mapping, by the computing device 202, each of the converted one or more sets of words of each of the plurality of input queries with the corresponding one or more sets of words of each of the plurality of input queries.
[0044] In some embodiments, the method 300 further includes receiving, by the computing device 202, the plurality of input queries. At least one set of words from the one or more sets of words of each of the plurality of input queries has a spelling error. In some embodiments, the method 300 further includes receiving, by the computing device 202, corrected words corresponding to the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error. In some embodiments, the method 300 further includes mapping, by the computing device 202, the corrected words with the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error.
[0045] FIG. 3B illustrates a schematic flow diagram for a method 320 for processing a multi-script, multi-lingual query, according to an embodiment of the present disclosure. At step 322, the method 320 includes receiving, by a computing device 202, an input query from a user device. The input query includes a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages. The input query includes a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language. The first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language. At step 324, the method 320 includes, for the one or more sets of words in the respective one or more languages different from the primary language, converting, by the computing device 202, scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language. At step 326, the method 320 includes, for the one or more sets of words in the respective one or more languages different from the primary language, translating, by the computing device 202, the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language. In some embodiments, translating the one or more sets of words in the respective one or more scripts different from the first script further includes transliterating, by the computing device 202, the one or more sets of words in the respective one or more scripts different from the first script from the respective one or more languages different from the primary language to the primary language.
[0046] At step 328, the method 320 further includes generating, by the computing device 202, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language. At step 330, the method 320 further includes analyzing, by the computing device 202, the translated input query to determine a target token. In some embodiments, analyzing the translated input query further includes comparing, by the computing device 202, the translated input query with a dataset stored in a database 106, and mapping, by the computing device 202, the translated input query with the dataset to determine the target token.
[0047] FIG. 4 illustrates an exemplary table 400 showing demonstrations of the method to generate a translated query from an input query. The first column indicates examples of the input queries, the second column indicates examples of translated queries according to conventional translation methodologies, and the last column indicates examples of the translated queries generated according to the method 300. As can be observed, the method 300 generates more accurate translated queries that may be analyzed to generate target tokens.
[0048] FIG. 5 illustrates a hardware platform 500 for implementation of the disclosed system 200, according to an example embodiment of the present disclosure. For the sake of brevity, construction, and operational features of the system 200 which are explained in detail above are not explained in detail herein. Particularly, computing machines such as but not limited to internal/external server clusters, quantum computers, desktops, laptops, smartphones, tablets, and wearables which may be used to execute the system 200 or may include the structure of the hardware platform 500. As illustrated, the hardware platform 500 may include additional components not shown, and that some of the components described may be removed and/or modified. For example, a computer system with multiple GPUs may be located on external-cloud platforms including Amazon® Web Services, or internal corporate cloud computing clusters, or organizational computing resources, etc.
[0049] The hardware platform 500 may be a computer system such as the system 200 that may be used with the embodiments described herein. The computer system may represent a computational platform that includes components that may be in a server or another computer system. As shown in FIG. 5, a computer system 500 can include an external storage device 510, a bus 520, a main memory 530, a read only memory 540, a mass storage device 550, communication port 560, and a processor 570. A person skilled in the art will appreciate that the computer system may include more than one processor and communication ports. Examples of processor 570 include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on chip processors or other future processors. Processor 570 may include various modules associated with embodiments of the present invention. Communication port 560 can be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fibre, a serial port, a parallel port, or other existing or future ports. Communication port 560 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects. Memory 530 can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read-only memory 540 can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor 570. Mass storage 550 may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7102 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc.
[0050] Bus 520 communicatively couples processor(s) 570 with the other memory, storage, and communication blocks. Bus 520 can be, e.g., a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 570 to software system.
[0051] Optionally, operator and administrative interfaces, e.g., a display, keyboard, and a cursor control device, may also be coupled to bus 520 to support direct operator interaction with a computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port 560. The external storage device 510 can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc-Re-Writable (CD-RW), Digital Video Disk-Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0052] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the invention and not as limitation.

ADVANTAGES OF INVENTION
[0053] The present invention provides a method and a system for processing a multi-script, multi-lingual query.
[0054] The present invention provides a method and system that does not require substantially additional memory for processing a multi-script, multi-lingual query.
[0055] The present invention provides a method and system that can be trained to improve accuracy of processing a multi-script, multi-lingual query.
 
, Claims:1. A method for processing a multi-script, multi-lingual query, the method comprising:
receiving, by a computing device, an input query from a user device, the input query comprising a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages, wherein the input query comprises a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language, and wherein the first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language;
for the one or more sets of words in the respective one or more languages different from the primary language:
converting, by the computing device, scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language; and
translating, by the computing device, the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language;
generating, by the computing device, from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language; and
analyzing, by the computing device, the translated input query to determine a target token.
2. The method as claimed in claim 1, wherein translating the one or more sets of words in the respective one or more scripts different from the first script further comprises transliterating, by the computing device, the one or more sets of words in the respective one or more scripts different from the first script from the respective one or more languages different from the primary language to the primary language.
3. The method as claimed in claim 1, wherein analyzing the translated input query further comprises:
comparing, by the computing device, the translated input query with a dataset stored in a database communicably coupled to the computing device; and
mapping, by the computing device, the translated input query with the dataset to determine the target token.
4. The method as claimed in claim 1, wherein the method further comprises generating, by the computing device, training data, and wherein generating training data comprises:
receiving, by the computing device, a plurality of input queries, each of the plurality of input queries comprising one or more sets of words in one or more languages different from the primary language, wherein the one or more sets of words in each of the plurality of input queries are in the first script associated with the primary language;
converting, by the computing device, scripts of the one or more sets of words of each of the plurality of input queries from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language; and
mapping, by the computing device, each of the converted one or more sets of words of each of the plurality of input queries with the corresponding one or more sets of words of each of the plurality of input queries.
5. The method as claimed in claim 4, further comprising;
receiving, by the computing device, the plurality of input queries, wherein at least one set of words from the one or more sets of words of each of the plurality of input queries has a spelling error;
receiving, by the computing device, corrected words corresponding to the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error; and
mapping, by the computing device, the corrected words with the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error.
6. A system for processing a multi-script, multi-lingual query, the system comprising:
a computing device comprising a processor communicably coupled with a memory, the memory storing instructions, which when executed by the processor, causes the computing device to be configured to:
receive an input query from a user device, the input query comprising a plurality of sets of words, each of the plurality of sets of words corresponding to a language from a plurality of languages, wherein the input query comprises a first set of words in a primary language and one or more sets of words in respective one or more languages different from the primary language, and wherein the first set of words in the primary language and the one or more sets of words in the respective one or more languages different from the primary language are in a first script associated with the primary language;
for the one or more sets of words in the respective one or more languages different from the primary language:
convert scripts of the one or more sets of words from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language; and
translate the converted one or more sets of words in the respective one or more scripts different from the first script, from the respective one or more languages different from the primary language to the primary language;
generate from the first set of words in the primary language, and the translated one or more sets of words in the primary language, a translated input query in the primary language; and
analyze the translated input query to determine a target token.
7. The system as claimed in claim 6, wherein to translate the one or more sets of words in the respective one or more scripts different from the first script, the computing device is further configured to transliterate the one or more sets of words in the respective one or more scripts different from the first script from the respective one or more languages different from the primary language to the primary language.
8. The system as claimed in claim 6, wherein to analyze the translated input query, the computing device is further configured to:
compare the translated input query with a dataset stored in a database communicably coupled to the computing device; and
map the translated input query with the dataset to determine the target token.
9. The system as claimed in claim 6, wherein the computing device is further configured to generate training data, and wherein, to generate training data, the computing device is configured to:
receive a plurality of input queries, each of the plurality of input queries comprising one or more sets of words in one or more languages different from the primary language, wherein the one or more sets of words in each of the plurality of input queries are in the first script associated with the primary language;
convert scripts of the one or more sets of words of each of the plurality of input queries from the first script to respective one or more scripts associated with the respective one or more languages different from the primary language; and
map each of the converted one or more sets of words of each of the plurality of input queries with the corresponding one or more sets of words of each of the plurality of input queries.
10. The system as claimed in claim 9, wherein the computing device is further configured to:
receive the plurality of input queries, wherein at least one set of words from the one or more sets of words of each of the plurality of input queries has a spelling error;
receive corrected words corresponding to the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error; and
map the corrected words with the at least one set of words from the one or more sets of words of each of the plurality of input queries having the spelling error.