A system and a method for evaluating music-based skills, aptitude and knowledge of a user

Abstract

A system (100) for evaluating music-based skills, aptitude and knowledge of a user is disclosed A receiving module (120) receives a request from the user for evaluating music-based skills, aptitude, and knowledge. A login module (125) queries the proficiency level of the user. An evaluation module (130) generates a test based on a response to the query. An aptitude assessment module (135) includes a recognition module (175) and a demonstration module (180). A knowledge assessment module (140) assesses the user based on music theory, timbre genre and associated musical topics. A skill assessment module (145) assesses the user based on vocals or an instrument. A customization module (150) customizes the test. A result generation module (155) generates the result. A feedback generation module (160) analyzes the performance of the user and generates feedback. A security measure module (165) verifies the identity of the user and secures integrity of the test.

Description

[0001] A SYSTEM AND A METHOD FOR EVALUATING MUSIC-BASED SKILLS, APTITUDE AND KNOWLEDGE OF A USER

[0002] EARLIEST PRIORITY DATE:

[0003] This Application claims priority from a complete patent application filed in India having Patent Application No. 202441030854, filed on April 17, 2024, and titled “A SYSTEM AND A METHOD FOR EVALUATING MUSIC-BASED SKILLS, APTITUDE AND KNOWLEDGE OF A USER”.

[0004] FIELD OF INVENTION

[0005] Embodiments of the present disclosure relate to the field of music education and more particularly, a system and a method for evaluating music-based skills, aptitude, and knowledge of a user.

[0006] BACKGROUND

[0007] Music education faces several significant obstacles, the lack of awareness and assessment of innate musicality being a primary concern. Many individuals who desire to learn music, regardless of their age, are often either unaware of their inherent musicality or hold perceptions of it that may not accurately reflect reality. Additionally, music educators or institutions often do not prioritize assessing this crucial aspect at the beginning of the musical education journey. Innate musicality is defined as an individual's natural, inherent, and often untaught ability to perceive, create, and interact with music. Providing a precise and universally accepted definition of innate musicality is challenging, but it generally entails an enhanced sensitivity to musical elements such as melody, rhythm, harmony, and timbre. People with innate musicality typically have an intuitive grasp of these components, even without formal education. Further, failing to assess a student's innate musicality can lead to issues such as student disillusionment, discontinuation of lessons, and strained relationships between teachers, students, and parents, negatively affecting the overall effectiveness of music education.

[0008] The challenge of choosing an instrument and managing expectations presents another hurdle in music education. Without early assessment of musical aptitude, students may face difficulties in selecting the right instrument or aligning their expectations with their actual musical abilities, potentially leading to frustration and discontinuation of their musical pursuits.

[0009] Limitations of traditional assessment methods also pose a significant challenge. Traditional assessments are crucial in any learning journey, including music, to monitor progress, provide feedback, and identify areas needing improvement. Traditional assessments, which depend on teachers or experts, are time-consuming and subject to biases and subjectivity. They can also induce stress in students, affecting the accuracy of the results.

[0010] International music boards like Associated Board of the Royal Schools of Music (ABRSM), London College of Music (LCM), and Trinity conduct proficiency exams based on specific curricula. However, such exams which include accepting prerecorded video submissions, still require individual evaluation. This is time-consuming and can be subject to bias.

[0011] Hence, there is a need for an improved system and method for evaluating music-based skills, aptitude, and knowledge of a user which addresses the aforementioned issue(s).

[0012] OBJECTIVES OF THE INVENTION

[0013] The primary objective of the invention is to create a digital platform for evaluating music-based skills, aptitude, and knowledge of a user using artificial intelligence. Another objective of the invention is to provide a musical evaluation based on recognition and demonstration of pitch and rhythm.

[0014] Another objective of the invention is to query the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced. The querying helps in tailoring assessments to match current level of musical skill of the user,

[0015] Yet another objective of the invention is to capture musical activities of the user such clapping, singing, or playing an instrument using a microphone and camera to facilitates the effective demonstration of the musical skills of the user.

[0016] Yet another objective of the invention is to provide the capability of an organizer to customize the assessment according to specific educational need.

[0017] Yet another objective of the invention is to integrate feedback, results, and reports generated through artificial intelligence and machine learning.

[0018] BRIEF DESCRIPTION

[0019] In accordance with an embodiment of the present disclosure, a system for evaluating music-based skills, aptitude and knowledge of a user is provided. The system includes a processing subsystem hosted on a server. The processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a receiving module. The receiving module is configured to receive a request from the user for evaluating at least one of music-based skills, aptitude, and knowledge of the user. The processing subsystem includes a login module operatively coupled to the receiving module. The login module is configured to query the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced. The processing subsystem includes an evaluation module operatively coupled to the login module. The evaluation module is configured to generate a test for the user based on a response to the said query. The test pertains to multiple levels of increasing difficulty. The evaluation module includes an aptitude assessment module. The aptitude assessment module includes a recognition module configured to enable the user to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file. Further, the aptitude assessment module includes a demonstration module operatively coupled to the recognition module. The demonstration module is configured to enable the user to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters. The demonstration module is also configured to record the demonstration using a microphone configured on a user device to evaluate the music-based aptitude level of the user. The evaluation module includes a knowledge assessment module operatively coupled to the aptitude assessment module. The knowledge assessment module is configured to assess the user based on music theory, timbre genre, and associated musical topics. The evaluation module includes a skill assessment module operatively coupled to the knowledge assessment module. The skill assessment module is configured to assess the user based on vocals or the instrument. The processing subsystem includes a customization module operatively coupled to the evaluation module. The customization module is configured to customize the test according to specific educational and evaluative requirements by an organizer. The processing subsystem includes a result generation module operatively coupled to the customization module. The result generation module is configured to generate a result of the test for evaluating music-based skills, aptitude, and knowledge of the user. The processing subsystem includes a feedback generation module operatively coupled to the result generation module. The feedback generation module configured to analyze a performance of the user with respect to the demonstration using an artificial intelligence model in real-time. The feedback generation module configured to generate feedback based on the analysis of the performance of the user using the artificial intelligence model in real-time. The processing subsystem includes a security measure module operatively coupled to the feedback generation module. The security measure module is configured to verify identity of the user by comparing one or more face features with a plurality of stored facial features of the user captured during the test using the artificial intelligence model. The security measure module is configured to secure integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

[0020] In accordance with another embodiment of the present disclosure, a method for evaluating music -based skills, aptitude and knowledge of a user is provided. The method includes receiving, by a receiving module, a request from the user for evaluating at least one of music-based skills, aptitude, and knowledge of the user. The method includes querying, by a login module, the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced. The method includes generating, by an evaluation module, a test for the user based on a response to the said query. The test pertains to multiple levels of increasing difficulty. The method includes enabling, by a recognition module of an aptitude assessment module, the user to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file. The method includes enabling, by a demonstration module of the aptitude assessment module, the user to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters. The method includes recording, by the demonstration module of the aptitude assessment module, the demonstration using a microphone configured on a user device to evaluate music -based aptitude level of the user. The method includes assessing, by a knowledge assessment module, the user based on music theory, timbre genre and associated musical topics. The method includes assessing, by a skill assessment module, the user based on vocals or the instrument. The method includes customizing, by a customization module, the test according to specific educational and evaluative requirements by an organizer. The method includes generating, by a result generation module, a result of the test for evaluating music-based skills, aptitude and knowledge of the user. Th method includes analyzing, by a feedback generation module, a performance of the user with respect to the demonstration using an artificial intelligence model in real-time. The method includes generating, by the feedback generation module, feedback based on the analysis of the performance of the user using the artificial intelligence model in real-time. The method includes verifying, by a security measure module, identity of the user by comparing one or more face features with a plurality of stored facial features of the user captured during the test using the artificial intelligence model. The method includes securing by the security measure module, integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

[0021] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

[0022] BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:

[0024] FIG. 1 is a block diagram representation of a system for evaluating music-based skills, aptitude and knowledge of a user in accordance with an embodiment of the present disclosure;

[0025] FIG. 2 is a schematic representation of a report for evaluating music-based skills, aptitude and knowledge of a user of FIG. 1 , in accordance with an embodiment of the present disclosure; FIG. 3 is an exemplary flow diagram for evaluating music-based skills, aptitude and knowledge of a user of FIG. 1 in accordance with an embodiment of the present disclosure;

[0026] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure;

[0027] FIG. 5(a) illustrates a flow chart representing the steps involved in a method for evaluating music-based skills, aptitude, and knowledge of a user in accordance with an embodiment of the present disclosure; and

[0028] FIG. 5(b) illustrates continued steps of the method of FIG. 5 (a) in accordance with an embodiment of the present disclosure.

[0029] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

[0030] DETAILED DESCRIPTION

[0031] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure. The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or subsystems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

[0033] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

[0034] Embodiments of the present disclosure relate to a system for evaluating music -based skills, aptitude and knowledge of a user. The system includes a processing subsystem hosted on a server. The processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a receiving module. The receiving module is configured to receive a request from the user for evaluating at least one of music-based skills, aptitude, and knowledge of the user. The processing subsystem includes a login module operatively coupled to the receiving module. The login module is configured to query the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced. The processing subsystem includes an evaluation module operatively coupled to the login module. The evaluation module is configured to generate a test for the user based on a response to the said query. The test pertains to multiple levels of increasing difficulty. The evaluation module includes an aptitude assessment module. The aptitude assessment module includes a recognition module configured to enable the user to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file. Further, the aptitude assessment module includes a demonstration module operatively coupled to the recognition module. The demonstration module is configured to enable the user to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters. The demonstration module is also configured to record the demonstration using a microphone configured on a user device to evaluate the musicbased aptitude level of the user. The evaluation module includes a knowledge assessment module operatively coupled to the aptitude assessment module. The knowledge assessment module is configured to assess the user based on music theory, timbre genre and associated musical topics. The evaluation module includes a skill assessment module operatively coupled to the knowledge assessment module. The skill assessment module is configured to assess the user based on vocals or the instrument. The processing subsystem includes a customization module operatively coupled to the evaluation module. The customization module is configured to customize the test according to specific educational and evaluative requirements by an organizer. The processing subsystem includes a result generation module operatively coupled to the customization module. The result generation module is configured to generate a result of the test for evaluating music-based skills, aptitude, and knowledge of the user. The processing subsystem includes a feedback generation module operatively coupled to the result generation module. The feedback generation module configured to analyze a performance of the user with respect to the demonstration using an artificial intelligence model in real-time. The feedback generation module configured to generate feedback based on the analysis of the performance of the user using the artificial intelligence model in real-time. The processing subsystem includes a security measure module operatively coupled to the feedback generation module. The security measure module is configured to verify identity of the user by comparing one or more face features with a plurality of stored facial features of the user captured during the test using the artificial intelligence model. The security measure module is configured to secure integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

[0035] FIG. 1 is a block diagram representation of a system (100) for evaluating music -based skills, aptitude, and knowledge of a user (175) in accordance with an embodiment of the present disclosure. The system (100) includes a processing subsystem (105) hosted on a server (108). In one embodiment, the server (108) may include a cloud-based server. In another embodiment, parts of the server (108) may be a local server coupled to a user device (170). The processing subsystem (105) is configured to execute on a network (115) to control bidirectional communications among a plurality of modules. In one example, the network (115) may be a private or public local area network (LAN) or Wide Area Network (WAN), such as the Internet. In another embodiment, the network (115) may include both wired and wireless communications according to one or more standards and / or via one or more transport mediums. In one example, the network (115) may include wireless communications according to one of the 802.11 or Bluetooth specification sets, or another standard or proprietary wireless communication protocol. In yet another embodiment, the network (115) may also include communications over a terrestrial cellular network, including, a global system for mobile communications (GSM), code division multiple access (CDMA), and / or enhanced data for global evolution (EDGE) network.

[0036] The processing subsystem (105) includes a receiving module (120). The receiving module (120) is configured to receive a request from the user (175) for evaluating at least one of music-based skills, aptitude, and knowledge of the user (175). Examples of the user includes, but is not limited to, a beginner, an aspirant, an advanced student, academic tutor, a professional musician, and the like. It must be noted that the system (100) does not necessitate the need for the presence of a teacher for the musical evaluation, when the said user (175) is a student. The music -based skills are referred to the practical abilities that the user (175) possesses to perform specific musical tasks or activities, including proficiencies such as playing an instrument and vocalizing with precise pitch and tone, and the like. The music -based aptitude refers to innate potential of the user (175) to understand, process, and learn musical concepts quickly and effectively. The music-based aptitude facilitates ear testing of the user for music, including abilities such as identifying pitches and recognizing melodies, and the like. Further, the music-based knowledge refers to the theoretical understanding that the user (175) has for music, including familiarity with music theory, various styles genres and associated musical topics.

[0037] In one embodiment, the receiving module (120) utilizes application programming interfaces (APIs) and machine learning (ML) tools to accurately recognize and interpret an input from the user (175) in real-time. The input is referred to any data that is received by the receiving module from the user. The examples of the input include text, audio, video, commands entered by the user and the like.

[0038] The processing subsystem (105) includes a login module (125) operatively coupled to the receiving module (120). Upon successfully receiving a request from the user (175), the system (100) initiates a registration process managed by a login module (125). During the registration process, the login module (125) query the user (175) in relation to a proficiency level of at least one of a musical skill and the instrument. The proficiency level is one of a beginner, intermediate and advanced. Examples of the instruments include, but are not limited to, guitar, keyboard, violin, drums and flute. In an embodiment, the proficiency level of at least one of a musical skill and the instrument at the time of the registration can be dynamically adjusted by the user (175) to reflect their improvement over time.

[0039] The processing subsystem (105) includes an evaluation module (130) operatively coupled to the login module (125). The evaluation module (130) is configured to generate a test for the user (175) based on a response to the said query. The test pertains to multiple levels of increasing difficulty and includes various aspects of music theory, practical skills, and aptitude.

[0040] In one embodiment, the test may include a diverse set of evaluation methods, including multiple choice questions (MCQs), sample musical video and audio for identification, descriptive questions, performance tasks, ear training exercises, and the like.

[0041] The evaluation module (130) includes an aptitude assessment module (135). The aptitude assessment module (135) includes a recognition module (175) configured to enable the user (175) to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file. The plurality of parameters comprises rhythm and pitch. The rhythm-related questions aim to understand the ability of the user (175) to discern different rhythmic patterns, tempo variations, and the like presented in the audio or video music file. The pitch-related questions are designed to assess the capacity of the user (175) for pitch recognition and melody identification.

[0042] In one embodiment, the recognition module (175) is configured to evaluate the ability of the user (175) to identify musical genres and styles from audio samples provided in the test.

[0043] Further, the aptitude assessment module (135) includes a demonstration module (180) operatively coupled to the recognition module (175). The demonstration module (180) is configured to enable the user (175) to demonstrate the audio or video music file vocally by clapping, singing, or playing an instrument corresponding to the plurality of parameters. The demonstration module (180) is also configured to record the demonstration using a microphone configured on the user device (170) to evaluate the music-based aptitude level of the user (175). The demonstration facilitates real-time evaluation of the user's performance.

[0044] It is to be noted that the user device (170) may comprise, but is not limited to, a mobile phone, desktop computer, portable digital assistant (PDA), smart phone, tablet, ultrabook, netbook, laptop, multi-processor system, microprocessor-based or programmable consumer electronic system, or any other communication device that a user may use. In some embodiments, the user device (170) may comprise a display module (not shown) to display information (for example, in the form of user interfaces). In further embodiments, the user device (170) may comprise one or more of touch screens, accelerometers, gyroscopes, cameras, microphones, global positioning system (GPS) devices, and so forth.

[0045] The evaluation module (130) includes a knowledge assessment module (140) operatively coupled to the aptitude assessment module (135). The knowledge assessment module (140) is configured to assess the user (175) based on music theory, timbre, genre, and associated musical topics. Th music theory is the study of the fundamental elements that construct and govern the language of music, including notes, scales, chords, rhythm, melody, harmony, and form. Assessing the user (175) based on music theory focuses on the user's familiarity with the language of music. The timbre is the sound quality, or tone quality, of a note played on the instrument. The genre is a conventional category that identifies some pieces of music as belonging to a shared tradition or set of conventions.

[0046] The evaluation module (130) includes a skill assessment module (145) operatively coupled to the knowledge assessment module (140). The skill assessment module (145) is configured to assess the user (175) based on vocals or the instrument. The processing subsystem (105) includes a customization module (150) operatively coupled to the evaluation module (130). The customization module (150) is configured to customize the test according to specific educational and evaluative requirements by an organizer. Examples for the organizer includes, but is not limited to, music tutors, educational institutions, and the like.

[0047] The complexity and sensitivity of the test is adjusted based on the selected proficiency level of the user (175) or as recommended by the organizer. The customizable feature of the test allows the user (175) to adjust settings including the audio or melodies quality, duration of the test, subject of the test and the like.

[0048] In one embodiment, the customization module (150) incorporates an intuitive user interface allowing the organizer to select from a repository (185) of question types, including multiple choice questions, sample musical video and audio for identification, descriptive questions, performance tasks.

[0049] In another embodiment, the customization module (150) employs an artificial intelligence model to automatically adjust the test complexity.

[0050] The processing subsystem (105) includes a result generation module (155) operatively coupled to the customization module (150). The result generation module (155) is configured to generate a result of the test for evaluating music -based skills, aptitude, and knowledge of the user (175). The result presents the quantitative outcomes of the test. The result displayed may be in the form of visual indicators, graphical representations including charts or graphs and the like.

[0051] The processing subsystem (105) includes a feedback generation module (160) operatively coupled to the result generation module (155). The feedback generation module (160) configured to analyze a performance of the user (175) with respect to the demonstration using an artificial intelligence model in real-time. The feedback generation module (160) configured to generate feedback based on the analysis of the performance of the user (175) using the artificial intelligence model in real-time. The feedback to the user (175) includes a visual representation of a plurality of criteria. The plurality of criteria includes rhythm recognition, rhythm demonstration, pitch recognition and pitch demonstration for offering an overview of evaluating the musical aptitude, skill level, and knowledge of the user (175). The visual representations indicating a visual score of the plurality of criteria is rating from low to high. A high visual score indicates a strong musicality and proficiency, and a low visual score indicates a need for further ear training in rhythm and pitch. A high visual score in any specific area signifies proficiency in that criterion.

[0052] In one embodiment, the artificial intelligence model uses an artificial intelligence algorithm. Examples of the artificial intelligence algorithm include, but are not limited to, a Deep Neural Network (DNN), Convolutional Neural Network (CNN), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN) and Deep Q-Networks.

[0053] In one embodiment, the feedback generation module ( 160) is configured to use several plugins, APIs, Machine learning and Al tools to recognize, decipher and provide feedback on audio, video and selection-based inputs from the user.

[0054] The processing subsystem (105) includes a security measure module (165) operatively coupled to the feedback generation module (160). The security measure module (165) is configured to verify identity of the user (175) by comparing one or more face features with a plurality of stored facial features of the user (175) captured during the test using the artificial intelligence model. The security measure module (165) is configured to secure integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

[0055] In an embodiment, the security measure module (165) might employ facial recognition technology to continuously monitor the user (175) throughout the duration of the test. If the security measure module (165) detects a discrepancy between the current and stored facial features, then a violation is indicated, and the test is locked automatically.

[0056] In one embodiment, the security measure module (165) is configured to incorporate a variety of biometric verification methods. The biometric verification methods includes fingerprint recognition, iris scanning, and voice recognition, and the like to verify identity of the user (175).

[0057] Let's consider an example, a user says "X" who utilizes the system (100) to evaluate his / her music-based skills, aptitude, and knowledge. To begin, User X is required to register with the system (100). During the registration process, the login module (125) queries User X about his / her proficiency level in playing the piano, which is his / her instrument of choice. User X identifies as an intermediate pianist. Based on User X's response, the evaluation module (130) generates a customized test that includes a mix of multiple-choice questions, audio clips for pitch and rhythm identification, and more. The demonstration module (180) allows User X to demonstrate his / her skills by clapping, singing, or playing the piano, which is recorded using the microphone to evaluate User X's musical aptitude. The skill assessment module (145) evaluates User X's piano performance to assess his / her musical skills. Additionally, the knowledge assessment module (140) assesses User X on music theory, timbre, genre and associated musical topics, evaluating his / her musical knowledge. Upon completing the test, the feedback generation module (160), utilizing an Al model, analyzes User X's performance in real time. The feedback generation module (160), generates personalized feedback, including visual representations that indicate scores ranging from low to high, highlighting areas for improvement and noting high proficiency in rhythm recognition but suggesting further ear training for pitch accuracy. Throughout the test, the security measure module (165) verifies identity of User X.

[0058] In one embodiment, the various functional components of the system may reside on a single computer, or they may be distributed across several computers in various arrangements. The various components of the system may, furthermore, access one or more databases, and each of the various components of the system may be in communication with one another. Further, while the components of FIG. 1 are discussed in the singular sense, it will be appreciated that in other embodiments multiple instances of the components may be employed.

[0059] FIG. 2 is a schematic representation of a report (190) for evaluating music-based skills, aptitude and knowledge of a user of FIG. 1 , in accordance with an embodiment of the present disclosure. Typically, the report (190) is a feedback generated by the feedback generation module (160). The report (190) includes a visual representation of a plurality of criteria. The plurality of criteria includes rhythm recognition, rhythm demonstration, pitch recognition and pitch demonstration for offering an overview of evaluating the musical aptitude, skill level, and knowledge of the user. Further, each of the plurality of criteria are represented with a visual score ranging from Tow’ to ‘high’. A high visual score indicates a strong musicality and proficiency, and a low visual score indicates a need for further ear training in rhythm and pitch. A high visual score in any specific area signifies proficiency in that criterion.

[0060] As depicted in FIG. 2, the high visual score in rhythm recognition suggests that the user excels in learning percussive instrument. For the user with an interest in melody- driven instruments or voice, the report advises focusing on ear training for pitch recognition and demonstration to enhance musical capabilities of the user.

[0061] Further, consider that the report indicates that a user has obtained high scores on all the criteria. In such a case, the user has well developed musicality and can choose from melodic or percussive instruments or voice. Likewise, if the report indicates that the user has obtained less scores on all the criteria, it is recommended that the user takes up training on aspects of both rhythm and pitch to be able to pursue music learning formally. Let’s consider another scenario wherein the report indicates that a user has obtained high scores on pitch recognition while pitch demonstration shows a lower score. This shows that the user has high scores for melodic instruments. However, voice and pitch demonstration must be developed. Therefore, the user is recommended to focus on developing rhythmic aptitude through ear training.

[0062] FIG. 3 is an exemplary flow diagram (200) for evaluating music -based skills, aptitude and knowledge of a user of FIG. 1 in accordance with an embodiment of the present disclosure.

[0063] The flow diagram (200) depicts the various paths of evaluating music-based skills (210), aptitude (215) and knowledge (220) through the evaluation platform (205). The skill levels is assessed (210) for vocal (225) and instrument (230). The skill tests require the user to sing or play an instrument with the device microphone and camera turned on for the application to capture. The results and reports (255) are shared upon assessment. Likewise, the evaluation platform (205) can assess the aptitude of a user. The aptitude / innate musicality test involves two aspects namely, recognition and demonstration. The user is required to perform a pitch and rhythm recognition (235) and a pitch and rhythm demonstration (240). The rhythm recognition (235) requires the user to listen to a piece of reference or an audio question and playback, listen and select the right answers from a set of audio answers. This is done for both pitch and rhythm. The rhythm demonstration (240) requires the user listen to a piece of audio / melody and when prompted, sing out loud to replicate what they have heard for the application to capture through the device microphone. Alternatively, the user may also clap along with the reference audio track for the application to capture using the device microphone. The results and reports (255) upon assessment of the user’s aptitude is shared. Additionally, the evaluation platform (205) is accountable to assess musical knowledge (220) of the user. The musical knowledge (220) can be split across music theory (230) timbre / instrument, genre / style (235) and associated musical topics. The results and reports (255) upon assessing the user’s knowledge is shared.

[0064] It must be noted that the user may choose to take up one or more of the aptitude (215), skill (210) or knowledge assessment (220).

[0065] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (300) includes processor(s) (330), and memory (310) operatively coupled to the bus (320). The processor(s) (330), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.

[0066] The memory (310) includes several subsystems stored in the form of executable program which instructs the processor (330) to perform the method steps illustrated in FIG. 1. The memory (310) includes a processing subsystem (105) of FIG.l. The processing subsystem (105) further has following modules: receiving module (120), a login module (125), an evaluation module (130), a customization module (150), a result generation module (155), a feedback generation module (160), and a security measure module (165).

[0067] In accordance with an embodiment of the present disclosure, a system (100) for evaluating music-based skills, aptitude and knowledge of a user (175) is provided. The system (100) includes a processing subsystem (105) hosted on a server (108). The processing subsystem (105) is configured to execute on a network (115) to control bidirectional communications among a plurality of modules. The processing subsystem (105) includes a receiving module (120). The receiving module (120) is configured to receive a request from the user (175) for evaluating at least one of music-based skills, aptitude, and knowledge of the user (175). The processing subsystem (105) includes a login module (125) operatively coupled to the receiving module (120). The login module (125) is configured to query the user (175) in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced. The processing subsystem (105) includes an evaluation module (130) operatively coupled to the login module (125). The evaluation module (130) is configured to generate a test for the user (175) based on a response to the said query. The test pertains to multiple levels of increasing difficulty. The evaluation module (130) includes an aptitude assessment module (135). The aptitude assessment module (135) includes a recognition module (175) configured to enable the user (175) to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file. Further, the aptitude assessment module (135) includes a demonstration module (180) operatively coupled to the recognition module (175). The demonstration module (180) is configured to enable the user (175) to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters. The demonstration module (180) is also configured to record the demonstration using a microphone configured on a user device (170) to evaluate the music-based aptitude level of the user (175). The evaluation module (130) includes a knowledge assessment module (140) operatively coupled to the aptitude assessment module (135). The knowledge assessment module (140) is configured to assess the user (175) based on music theory, timbre genre and associated musical topics. The evaluation module (130) includes a skill assessment module (145) operatively coupled to the knowledge assessment module (140). The skill assessment module (145) is configured to assess the user (175) based on vocals or the instrument. The processing subsystem (105) includes a customization module (150) operatively coupled to the evaluation module (130). The customization module (150) is configured to customize the test according to specific educational and evaluative requirements by an organizer. The processing subsystem (105) includes a result generation module (155) operatively coupled to the customization module (150). The result generation module (155) is configured to generate a result of the test for evaluating music -based skills, aptitude, and knowledge of the user (175). The processing subsystem (105) includes a feedback generation module (160) operatively coupled to the result generation module (155). The feedback generation module ( 160) configured to analyze a performance of the user (175) with respect to the demonstration using an artificial intelligence model in realtime. The feedback generation module (160) configured to generate feedback based on the analysis of the performance of the user (175) using the artificial intelligence model in real-time. The processing subsystem (105) includes a security measure module (165) operatively coupled to the feedback generation module (160). The security measure module (165) is configured to verify identity of the user (175) by comparing one or more face features with a plurality of stored facial features of the user (175) captured during the test using the artificial intelligence model. The security measure module (165) is configured to secure integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

[0068] The bus (320) as used herein refers to internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (320) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bitserial format and the parallel bus transmits data across multiple wires. The bus (320), as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.

[0069] FIG. 5(a) illustrates a flow chart representing the steps involved in a method (400) for evaluating music-based skills, aptitude, and knowledge of a user in accordance with an embodiment of the present disclosure. FIG. 5 (b) illustrates continued steps of the method (400) of FIG. 5 (a) in accordance with an embodiment of the present disclosure. The method (400) includes receiving, by a receiving module, a request from the user for evaluating at least one of music-based skills, aptitude, and knowledge of the user in step 410. Examples of users includes, but is not limited to, a beginner, an aspirant, an advanced student, academic tutor, a professional musician, and the like. The musicbased skills refer to the practical abilities the user possesses to perform specific musical tasks or activities, including proficiencies such as playing an instrument and vocalizing with precise pitch and tone, and the like. The music -based aptitude refers to innate potential of the user to understand, process, and learn musical concepts quickly and effectively. Music -based knowledge refers to the theoretical understanding the user has of music, including familiarity with music theory, various styles genres and associated musical topics.

[0070] The method (400) includes querying, by a login module, the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration. The proficiency level is one of a beginner, intermediate and advanced in step 415. Examples of instruments include, but are not limited to, guitar, keyboard, violin, drums, flute, and the like.

[0071] In an embodiment, the proficiency level of at least one of a musical skill and the instrument at the time of the registration can be dynamically adjusted by the user to reflect their improvement over time.

[0072] The method (400) includes generating, by an evaluation module, a test for the user based on a response to the said query. The test pertains to multiple levels of increasing difficulty in step 420. In one embodiment, the test may include a diverse set of evaluation methods, including multiple choice questions (MCQs), sample musical video and audio for identification, descriptive questions, performance tasks, ear training exercises, and the like.

[0073] The method (400) includes enabling, by a recognition module of an aptitude assessment module (135), the user to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file in step 425. The plurality of parameters comprises rhythm and pitch. The rhythm-related questions aim to understand the ability of the user to discern different rhythmic patterns, tempo variations, and the like presented in the audio or video music file. The pitch-related questions are designed to assess capacity of the user for pitch recognition and melody identification.

[0074] The method (400) includes enabling, by a demonstration module of the aptitude assessment module, the user to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters in step 430.

[0075] The method (400) includes recording, by the demonstration module of the aptitude assessment module, the demonstration using a microphone configured on a user device to evaluate music-based aptitude level of the user in step 435.

[0076] The method (400) includes assessing, by a knowledge assessment module, the user based on music theory, timbre genre, and associated musical topics in step 440.

[0077] The method (400) includes assessing, by a skill assessment module, the user based on vocals or the instrument in step 445.

[0078] The method (400) includes customizing, by a customization module, the test according to specific educational and evaluative requirements by an organizer in step 450. Examples of the organizer includes, but is not limited to, music tutors, educational institutions, and the like.

[0079] The complexity and sensitivity of the test is adjusted based on selected proficiency level of the user or as recommended by the organizer. The customizable feature of the test allows the user to adjust settings including the audios or melodies quality, duration of the test, subject of the test and the like. In one embodiment, the customization module incorporates an intuitive user interface allowing organizer to select from a repository of question types, including multiple choice questions, sample musical video and audio for identification, descriptive questions, performance tasks.

[0080] In another embodiment, the customization module employs artificial intelligence to automatically adjust the test complexity.

[0081] The method (400) includes generating, by a result generation module, a result of the test for evaluating music-based skills, aptitude and knowledge of the user in step 455.

[0082] Th method (400) includes analyzing, by a feedback generation module, the performance of the user with respect to the demonstration using an artificial intelligence model in real-time in step 460.

[0083] The method (400) includes generating, by the feedback generation module, feedback based on the analysis of the performance of the user using the artificial intelligence model in real-time in step 465. The feedback to the user includes a visual representation of a plurality of criteria. The plurality of criteria includes rhythm recognition, rhythm demonstration, pitch recognition and pitch demonstration for offering an overview of evaluating the musical aptitude, skill level, and knowledge of the user. The visual representations indicating a visual score of the plurality of criteria is rating from low to high. A high visual score indicates a strong musicality and proficiency, and a low visual score indicates a need for further ear training in rhythm and pitch. A high visual score in any specific area signifies proficiency in that criterion.

[0084] The method (400) includes verifying, by a security measure module, identity of the user by comparing one or more face features with a plurality of stored facial features of the user captured during the test using the artificial intelligence model in step 470. In one embodiment, the security measure module incorporates a variety of biometric verification methods. This includes fingerprint recognition, iris scanning, and voice recognition, and the like to verify identity of the user.

[0085] The method (400) includes securing by the security measure module, integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure in step 475. In an embodiment, the security measure module might employ facial recognition technology to continuously monitor the user throughout the duration of the test. If the security measure module detects a discrepancy between the current and stored facial features, indicating a violation and automatically locks the test.

[0086] Use case 1 : Consider that a guitar teacher finds out prior to the lessons that a student is weak on the rhythm front. This could be a potential reason for the learning. Therefore, the guitar teacher works with the student primarily on rhythm lessons prior to starting the guitar lessons.

[0087] Use case 2: Consider an enthusiastic aspirant who desires to learn music but does not have a specific preference or a clear idea at the time of enquiry. Through the assessment, the rhythm sense is gauged to be stronger than sensitivity to melody, therefore a percussive instrument like the drum kit is recommended. However, in case both rhythm and melody sensitivity emerged stronger, the aspirant would have a wider choice of instrument and can make a more subjective or emotion based decision with a very good chance of continued learning.

[0088] Use case 3: Consider parents of a child who have approached a music school to enroll their child for singing lessons. The parents believe that their child is naturally talented. However, a teacher upon interacting and listening to the child’s singing recognizes that there are basic problems with pitching (melody) and timing (rhythm). The same is communicated to the parents and the child takes lessons to overcome the basic problems. Various embodiments of the system and method for evaluating music -based skills, aptitude, and knowledge of a user as described above provide a highly customizable test. This customization enables organizers to create tests to meet diverse educational needs and goals. By querying users about their proficiency level in music skills or instruments at registration, the invention personalizes the learning and assessment process to cater to individual needs. The system's ability to assess musical performance through actions such as clapping, singing, or playing an instrument, captured via microphone, plays a crucial role in evaluating the user's practical skills. Integrating artificial intelligence and machine learning for feedback generation, the system allows for real-time performance analysis. Additionally, the system behaves as an on demand assistant. Furthermore, the security measure module, which employs advanced biometric verification methods, ensures that assessments are completed by the registered user, thus maintaining the integrity of the evaluation process.

[0089] Further, the system and method described herein frees up time, resources and infrastructure for teachers and institutions thereby making it time and cost effective.

[0090] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing subsystem” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A control unit including hardware may also perform one or more of the techniques of this disclosure.

[0091] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules, or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components.

[0092] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.

[0093] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

[0094] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.

Claims

I CLAIM:

1. A system (100) for evaluating music-based skills, aptitude and knowledge of a user (175) comprising: characterized in that, a processing subsystem (105) hosted on a server (108) and configured to execute on a network (115) to control bidirectional communications among a plurality of modules, wherein the plurality of modules comprising: a receiving module (120) configured to receive a request from the user (175) for evaluating at least one of music-based skills, aptitude, and knowledge of the user (175); a login module (125) operatively coupled to the receiving module (120), wherein the login module (125) is configured to query the user (175) in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration, wherein the proficiency level is one of a beginner, intermediate and advanced; an evaluation module (130) operatively coupled to the login module (125) wherein the evaluation module (130) is configured to generate a test for the user (175) based on a response to the said query wherein the test pertains to multiple levels of increasing difficulty wherein the evaluation module (130) comprises: an aptitude assessment module (135) comprising: a recognition module (175) configured to enable the user (175) to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file; and a demonstration module ( 180) operatively coupled to the recognition module (175) wherein the demonstration module (180) is configured to:enable the user (175) to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters; and record the demonstration using a microphone configured on a user device (170) to evaluate musicbased aptitude level of the user (175); a knowledge assessment module (140) operatively coupled to the aptitude assessment module (135), wherein the knowledge assessment module (140) is configured to assess the user (175) based on music theory, timbre genre and associated musical topics; and a skill assessment module (145) operatively coupled to the knowledge assessment module (140) wherein the skill assessment module (145) is configured to assess the user (175) based on vocals or the instrument; a customization module (150) operatively coupled to the evaluation module (130), wherein the customization module (150) is configured to customize the test according to specific educational and evaluative requirements by an organizer; a result generation module (155) operatively coupled to the customization module (150), wherein the result generation module (155) is configured to generate a result of the test for evaluating music-based skills, aptitude and knowledge of the user (175); a feedback generation module (160) operatively coupled to the result generation module (155), wherein the feedback generation module (160) configured to: analyze a performance of the user (175) with respect to the demonstration using an artificial intelligence model in real-time; andgenerate feedback based on the analysis of the performance of the user (175) using the artificial intelligence model in real-time; and a security measure module (165) operatively coupled to the feedback generation module (160), wherein the security measure module (165) is configured to: verify identity of the user (175) by comparing one or more face features with a plurality of stored facial features of the user (175) captured during the test using the artificial intelligence model; and secure integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure.

2. The system (100) as claimed in claim 1, wherein the user (175) is categorized as one of a beginner, an aspirant, an advanced student, academic tutor, and a professional musician.

3. The system (100) as claimed in claim 1, wherein the receiving module (120) utilizes application programming interfaces and machine learning tools to accurately recognize and interpret input from the user (175) in real-time.

4. The system (100) as claimed in claim 1, wherein the plurality of parameters comprises rhythm and pitch.

5. The system (100) as claimed in claim 1, wherein the recognition module (175) is configured to evaluate the ability of the user (175) to identify musical genres and styles from audio samples provided in the test.

6. The system (100) as claimed in claim 1, wherein the complexity and sensitivity of the test is adjusted based on selected proficiency level of the user (175) or as recommended by the organizer.

7. The system (100) as claimed in claim 1, wherein the test is customizable, thereby allowing user (175) to adjust settings including the set of audios or the set of melodies quality, duration of the test, and subject of the test.

8. The system (100) as claimed in claim 1, wherein the feedback to the user (175) comprises a visual representation of a plurality of criteria, wherein the plurality of criteria comprises rhythm recognition, rhythm demonstration, pitch recognition and pitch demonstration for offering an overview of evaluating the musical aptitude, skill level, and knowledge of the user (175).

9. The system (100) as claimed in claim 8, wherein the visual representations indicating a visual score of the plurality of criteria is rating from low to high, wherein a high visual score indicates a strong musicality and proficiency and a low visual score, indicates a need for further ear training in rhythm and pitch, wherein the high visual score in any specific area signifies proficiency in that criterion.

10. The system (100) as claimed in claim 1, wherein the customization module (150) is configured with an intuitive user interface to allow the organizer to select from a repository (185) of question types, including multiple choice questions, sample musical video and audio for identification, descriptive questions, performance tasks.

11. A method (400) for evaluating music-based skills, aptitude and knowledge of a user comprising:characterized in that, receiving, by a receiving module, a request from a user for evaluating at least one of music-based skills, aptitude, and knowledge of the user; (410) querying, by a login module, the user in relation to a proficiency level of at least one of a musical skill and an instrument at the time of registration, wherein the proficiency level is one of a beginner, intermediate and advanced; (415) generating, by an evaluation module, a test for the user based on a response to the said query wherein the test pertains to multiple levels of increasing difficulty; (420) enabling, by a recognition module of an aptitude assessment module, the user to respond to a plurality of questions based on a plurality of parameters associated to an audio or video music file; (425) enabling, by a demonstration module of the aptitude assessment module, the user to demonstrate the audio or video music file by clapping, singing, or playing an instrument corresponding to the plurality of parameters; (430) recording, by the demonstration module of the aptitude assessment module, the demonstration using a microphone configured on a user device to evaluate music -based aptitude level of the user; (435) assessing, by a knowledge assessment module, the user based on music theory, timbre genre, and associated musical topics; (440) assessing, by a skill assessment module, the user based on vocals or the instrument; (445) customizing, by a customization module, the test according to specific educational and evaluative requirements by an organizer; (450) generating, by a result generation module, a result of the test for evaluating music-based skills, aptitude and knowledge of the user; (455)analyzing, by a feedback generation module, a performance of the user with respect to the demonstration using an artificial intelligence model in real-time; (460) generating, by the feedback generation module, feedback based on the analysis of the performance of the user using the artificial intelligence model in real-time; (465) verifying, by a security measure module, identity of the user by comparing one or more face features with a plurality of stored facial features of the user captured during the test using the artificial intelligence model; and (470) securing by the security measure module, integrity of the test by locking the test and alerting the organizer in an occurrence of a verification failure. (475)

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