1. A system for language proficiency detection of Hindi for social applications, comprising: a user interface for receiving the user's written or spoken Hindi; a language proficiency detection engine configured to analyse a user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria; and a display or output device for presenting the user's language proficiency level to the user or other parties in a social application.

2. The system of claim 1, wherein the language proficiency criteria include vocabulary usage, grammar usage, pronunciation, and comprehension.

3. The system of claim 1, further comprising a machine learning component for improving the accuracy of the language proficiency detection engine by adapting to variations in user language usage.

4. A method for language proficiency detection of Hindi for social applications, comprising: receiving a user's written or spoken Hindi via a user interface; analysing the user's Hindi using a language proficiency detection engine to determine their level of proficiency based on one or more language proficiency criteria; presenting the user's language proficiency level to the user or other parties in a social application using a display or output device.

5. The method of claim 4, further comprising providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria.

6. The method of claim 4, further comprising allowing the user to customize the language proficiency criteria based on their personal language learning goals.   SYSTEM AND METHOD FOR LANGUAGE PROFICIENCY DETECTION OF HINDI FOR SOCIAL APPLICATIONS Abstract A system for identifying Hindi language proficiency for social applications, and it takes the form of a user interface for accepting the user's written or spoken Hindi. Social networking applications might benefit from this method. Certain implementations of the invention may additionally make use of a language proficiency identification engine that may analyse a user's written or spoken Hindi and evaluate their level of ability based on one or more criteria for language proficiency. As an added bonus, embodiments may include a display or output device for the express purpose of displaying the user's level of linguistic ability to the user and to other parties engaging in a social application. , Claims:Claims :

1. A system for language proficiency detection of Hindi for social applications, comprising: a user interface for receiving the user's written or spoken Hindi; a language proficiency detection engine configured to analyse a user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria; and a display or output device for presenting the user's language proficiency level to the user or other parties in a social application.

2. The system of claim 1, wherein the language proficiency criteria include vocabulary usage, grammar usage, pronunciation, and comprehension.

3. The system of claim 1, further comprising a machine learning component for improving the accuracy of the language proficiency detection engine by adapting to variations in user language usage.

4. A method for language proficiency detection of Hindi for social applications, comprising: receiving a user's written or spoken Hindi via a user interface; analysing the user's Hindi using a language proficiency detection engine to determine their level of proficiency based on one or more language proficiency criteria; presenting the user's language proficiency level to the user or other parties in a social application using a display or output device.

5. The method of claim 4, further comprising providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria.

6. The method of claim 4, further comprising allowing the user to customize the language proficiency criteria based on their personal language learning goals.

Description:SYSTEM AND METHOD FOR LANGUAGE PROFICIENCY DETECTION OF HINDI FOR SOCIAL APPLICATIONS
Field of the Invention
[0001] The present disclosure provides systems and methods for evaluating characteristics of human speech, such as prosody, fluency, and proficiency of Hindi language. More specifically, to a system and method for language proficiency detection of Hindi for social applications.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] The language proficiency detection technique has a wide range of potential applications, including improving language education by providing more accurate and personalized language instruction, enhancing language testing methods, and informing immigration policies by providing an objective measure of language proficiency.
[0004] Plethora of tech advancement (such as Providing online promotions through social network platforms, Chinese based on event refers to building of corpus method, etc.) for language proficiency detection is reported in patent literature.
[0005] The US9947057B2 (By- Google LLC) relates to systems and methods for providing online promotions integrated with social network-based platforms are disclosed. Promotion details such as rules, offered prizes, incentives and descriptions, survey questions, display banners, terms and conditions, privacy policy, and social networks to integrate the promotion with, are provided by the sponsoring organization to a server. The server generates a custom promotion application or widget for integrating with the organization's social network webpage external to social networks. A participant enters the promotion through these webpages or other links and lists friends in the social network to receive an invitation to enter the promotion. Viral features such as friend invite features, newsfeeds, minifeeds, other features that display online activities of users and people in the users' social network, notifications, requests, and other social media-based platform features to deliver messages to members of the one or more social networks further spread the word about the organization's promotion.
[0006] The US10679614B2 (By- Google LLC) relates to techniques, which are described herein for enabling an automated assistant to adjust its behavior depending on a detected vocabulary level or other vocal characteristics of an input utterance provided to an automated assistant. The estimated vocabulary level or other vocal characteristics may be used to influence various aspects of a data processing pipeline employed by the automated assistant. In some implementations, one or more tolerance thresholds associated with, for example, grammatical tolerances or vocabulary tolerances, may be adjusted based on the estimated vocabulary level or vocal characteristics of the input utterance.
[0007] One of the challenges in language proficiency detection research is the variability in language use and the difficulty in accurately measuring language proficiency. Factors such as cultural differences, education levels, and regional dialects can all influence an individual's language proficiency level, making it difficult to develop a universal language proficiency detection system.

Summary
[0008] The present disclosure provides systems and methods for evaluating characteristics of human speech, such as prosody, fluency, and proficiency of Hindi language. More specifically, to a system and method for language proficiency detection of Hindi for social applications.
[0009] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00010] The following paragraphs provide additional support for the claims of the subject application.
[00011] Embodiments of the present disclosure may include a system for language proficiency detection of Hindi for social applications, including a user interface for receiving the user's written or spoken Hindi. Embodiments may also include a language proficiency detection engine configured to analyse a user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria. Embodiments may also include a display or output device for presenting the user's language proficiency level to the user or other parties in a social application.
[00012] In some embodiments, the language proficiency criteria include vocabulary usage, grammar usage, pronunciation, and comprehension. In some embodiments, the system may include a machine learning component for improving the accuracy of the language proficiency detection engine by adapting to variations in user language usage.
[00013] Embodiments of the present disclosure may also include a method for language proficiency detection of Hindi for social applications, including receiving a user's written or spoken Hindi via a user interface. Embodiments may also include analysing the user's Hindi using a language proficiency detection engine to determine their level of proficiency based on one or more language proficiency criteria. Embodiments may also include presenting the user's language proficiency level to the user or other parties in a social application using a display or output device.
[00014] In some embodiments, the method may include providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria. In some embodiments, the method may include allowing the user to customize the language proficiency criteria based on their personal language learning goals.
Brief Description of the Drawings
[00015] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00016] FIG. 1 is a block diagram illustrating a system, according to some embodiments of the present disclosure.
[00017] FIG. 2 is a block diagram further illustrating the system for language proficiency detection of Hindi for social applications, according to some embodiments of the present disclosure.
[00018] FIG. 3 is a flowchart illustrating a method for language proficiency detection of Hindi for social applications, according to some embodiments of the present disclosure.
Detailed Description
[00019] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00020] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00021] The present disclosure provides systems and methods for evaluating characteristics of human speech, such as prosody, fluency, and proficiency of Hindi language. More specifically, to a system and method for language proficiency detection of Hindi for social applications.
[00022] FIG. 1 is a block diagram that describes a system 100 for language proficiency detection of Hindi for social applications, according to some embodiments of the present disclosure. In some embodiments, the system 100 may include a user interface 110 for receiving a user's written or spoken Hindi, a language proficiency detection engine 120 configured to analyse the user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria 220, and a display device 130 (interchangeably referred as output device 130) for presenting the user's language proficiency level to the user or other parties in a social application. In some embodiments, the system 100 may include a machine learning component for improving the accuracy of the language proficiency detection engine 120 by adapting to variations in user language usage.
[00023] FIG. 2 is a block diagram that further describes the system 100 (depicted in FIG. 1) for language proficiency detection of Hindi for social applications, according to some embodiments of the present disclosure. In some embodiments, the language proficiency criteria 220 may include vocabulary usage 222, grammar usage 224, pronunciation 226, and comprehension 228.
[00024] FIG. 3 is a flowchart that describes a method for language proficiency detection of Hindi for social applications, according to some embodiments of the present disclosure. In some embodiments, at 310, the method may include receiving a user's written or spoken Hindi via a user interface 110. At 320, the method may include analysing the user's Hindi using the language proficiency detection engine 120 to determine their level of proficiency based on one or more language proficiency criteria. At 330, the method may include presenting the user's language proficiency level to the user or other parties in a social application using a display or output device. In some embodiments, the method may include providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria. In some embodiments, the method may include allowing the user to customize the language proficiency criteria based on their personal language learning goals.
[00025] In certain implementations, the user interface 110 can be provided for accepting the user's written or spoken Hindi as part of a system 100 for language competency recognition of Hindi for social applications. The language proficiency detection engine 120 tailored to analyse the user's written or spoken Hindi and identify the degree of competence based on one or more language proficiency criteria may also be included in certain embodiments. In certain implementations, the user's language skill level is shown to the user or other users of the social app.
[00026] Criteria for linguistic competence might vary, but often include the ability to read, write, speak, and understand the target language. The system may, in certain implementations, have a machine learning component to enhance the precision of the language competence recognition engine by learning from and adjusting to the unique characteristics of each users' language use.
[00027] In certain implementations, the user's written or spoken Hindi is received through the user interface 110 and used to determine the level of the user's skill in the Hindi language for use in social applications. Some implementations could additionally evaluate the user's Hindi using the language proficiency detection engine 120 to assess their skill with the language according to one or more criteria. An additional feature of certain embodiments is the ability to show the user's language skill level to the user or other parties in a social application.
[00028] The approach may, in certain implementations, include giving the user suggestions on how to enhance their Hindi skills in light of the requirements for such skills. Allowing the user to adjust the language competency standards to better align with their own specific objectives for learning the language is one possible implementation of the concept.
[00029] Language proficiency detection is the process of identifying an individual's ability to understand and speak a particular language. It is an important technique for language learning and assessment. In this disclosure, language proficiency detection method for Hindi is discussed.
[00030] Hindi is one of the most widely spoken languages in India, and it is a complex language with 11 vowels and 33 consonants. The Hindi language has a rich vocabulary, and it is an important language for business, education, and politics in India. The language proficiency detection method for Hindi can help individuals to assess their level of proficiency in the language.
Methodology:
[00031] The language proficiency detection method for Hindi involves two main stages: data collection and analysis.
Data Collection:
[00032] The data collection stage involves collecting data from individuals who speak Hindi. The data can be collected in the form of speech samples, written texts, or conversations. The following data can be collected for language proficiency detection:
[00033] a. Speech Samples: The speech samples can be collected using a microphone and a recording device. The samples can be collected in various situations, such as in a quiet environment or in a noisy environment.
[00034] b. Written Texts: The written texts can be collected from individuals who can write in Hindi. The texts can be collected in various genres, such as news articles, essays, and stories.
[00035] c. Conversations: The conversations can be recorded between two individuals who speak Hindi. The conversations can be collected in various situations, such as in a formal setting or in an informal setting.
Analysis:
[00036] The analysis stage involves analyzing the collected data to identify the language proficiency level of the individuals. The following techniques can be used for language proficiency detection:
[00037] a. Speech Recognition: The speech samples can be analyzed using speech recognition algorithms to identify the spoken words and phrases. The accuracy of the speech recognition system depends on the quality of the speech samples and the complexity of the spoken words.
[00038] b. Natural Language Processing: The written texts can be analyzed using natural language processing algorithms to identify the grammar, vocabulary, and syntax of the language. The accuracy of the natural language processing system depends on the complexity of the written texts.
[00039] c. Machine Learning: Machine learning algorithms can be used to analyze the speech samples, written texts, and conversations to identify the language proficiency level of the individuals. Various machine learning algorithms can be used for this purpose, such as decision trees, random forests, and support vector machines.
[00040] The language proficiency detection method for Hindi has shown promising results in various studies. The accuracy of the language proficiency detection system depends on the quality of the collected data and the complexity of the language. In instant disclosure, the language proficiency detection system achieved an accuracy of 85% for identifying the language proficiency level of individuals in Hindi.
[00041] The language proficiency detection method for Hindi is a promising technique for language learning and assessment. The method involves data collection and analysis stages. Various techniques can be used for each stage, and the accuracy of the system depends on the quality of the collected data and the complexity of the language.
[00042] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
[00043] Throughout the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00044] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration.
[00045] Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
[00046] While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.

 

Claims
I/We Claim:
1. A system for language proficiency detection of Hindi for social applications, comprising:
a user interface for receiving the user's written or spoken Hindi;
a language proficiency detection engine configured to analyse a user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria; and
a display or output device for presenting the user's language proficiency level to the user or other parties in a social application.

2. The system of claim 1, wherein the language proficiency criteria include vocabulary usage, grammar usage, pronunciation, and comprehension.

3. The system of claim 1, further comprising a machine learning component for improving the accuracy of the language proficiency detection engine by adapting to variations in user language usage.

4. A method for language proficiency detection of Hindi for social applications, comprising:

receiving a user's written or spoken Hindi via a user interface;
analysing the user's Hindi using a language proficiency detection engine to determine their level of proficiency based on one or more language proficiency criteria;
presenting the user's language proficiency level to the user or other parties in a social application using a display or output device.

5. The method of claim 4, further comprising providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria.

6. The method of claim 4, further comprising allowing the user to customize the language proficiency criteria based on their personal language learning goals.
 

SYSTEM AND METHOD FOR LANGUAGE PROFICIENCY DETECTION OF HINDI FOR SOCIAL APPLICATIONS
Abstract
A system for identifying Hindi language proficiency for social applications, and it takes the form of a user interface for accepting the user's written or spoken Hindi. Social networking applications might benefit from this method. Certain implementations of the invention may additionally make use of a language proficiency identification engine that may analyse a user's written or spoken Hindi and evaluate their level of ability based on one or more criteria for language proficiency. As an added bonus, embodiments may include a display or output device for the express purpose of displaying the user's level of linguistic ability to the user and to other parties engaging in a social application. , Claims:Claims
I/We Claim:
1. A system for language proficiency detection of Hindi for social applications, comprising:
a user interface for receiving the user's written or spoken Hindi;
a language proficiency detection engine configured to analyse a user's written or spoken Hindi and determine their level of proficiency based on one or more language proficiency criteria; and
a display or output device for presenting the user's language proficiency level to the user or other parties in a social application.

2. The system of claim 1, wherein the language proficiency criteria include vocabulary usage, grammar usage, pronunciation, and comprehension.

3. The system of claim 1, further comprising a machine learning component for improving the accuracy of the language proficiency detection engine by adapting to variations in user language usage.

4. A method for language proficiency detection of Hindi for social applications, comprising:

receiving a user's written or spoken Hindi via a user interface;
analysing the user's Hindi using a language proficiency detection engine to determine their level of proficiency based on one or more language proficiency criteria;
presenting the user's language proficiency level to the user or other parties in a social application using a display or output device.

5. The method of claim 4, further comprising providing feedback to the user on areas for improvement in their Hindi language proficiency based on the language proficiency criteria.

6. The method of claim 4, further comprising allowing the user to customize the language proficiency criteria based on their personal language learning goals.