1. A system for language disorder screening, comprising: a user interface for presenting a language screening test to a user; a speech recognition module configured to record and transcribe the user's spoken responses to the language screening test; a language disorder screening module configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria; and a feedback module configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.

2. The system of claim 1, further comprising a database of language disorder screening criteria, which may include measures of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills.

3. The system of claim 1, wherein the feedback module is configured to provide detailed feedback to the user on their language disorder screening score, including an explanation of the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

4. The system of claim 1, further comprising a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information.

5. The system of claim 1, further comprising a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

6. A method for language disorder screening, comprising: presenting a language screening test to a user via a user interface; recording and transcribing the user's spoken responses to the language screening test using a speech recognition module; analysing the transcribed responses using a language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria; providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.

7. The method of claim 1, further comprising accessing a database of language disorder screening criteria, which may include measures of fluency, syntax, semantics, pragmatics, or other relevant language skills.

8. The method of claim 1, wherein providing feedback to the user on their language disorder screening score includes providing detailed feedback on the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

9. The method of claim 1, further comprising refining the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information.

10. The method of claim 1, further comprising storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results. Technique for Language disorder screening Abstract The instant disclosure elucidates a system for screening for language disorders is a user interface that delivers a language screening test to a user. Embodiments may also make use of a voice recognition module configured to record and transcribe the user's spoken responses to the language screening test. Embodiments may additionally include a language disorder screening module that is programmed to analyse the transcribed responses and provide a language disorder screening score based on one or more language disorder screening criteria. In certain implementations, the screening results are shown to the user together with suggestions for next steps depending on the results of the screening. , Claims:Claims :

1. A system for language disorder screening, comprising: a user interface for presenting a language screening test to a user; a speech recognition module configured to record and transcribe the user's spoken responses to the language screening test; a language disorder screening module configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria; and a feedback module configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.

2. The system of claim 1, further comprising a database of language disorder screening criteria, which may include measures of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills.

3. The system of claim 1, wherein the feedback module is configured to provide detailed feedback to the user on their language disorder screening score, including an explanation of the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

4. The system of claim 1, further comprising a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information.

5. The system of claim 1, further comprising a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

6. A method for language disorder screening, comprising: presenting a language screening test to a user via a user interface; recording and transcribing the user's spoken responses to the language screening test using a speech recognition module; analysing the transcribed responses using a language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria; providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.

7. The method of claim 1, further comprising accessing a database of language disorder screening criteria, which may include measures of fluency, syntax, semantics, pragmatics, or other relevant language skills.

8. The method of claim 1, wherein providing feedback to the user on their language disorder screening score includes providing detailed feedback on the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

9. The method of claim 1, further comprising refining the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information.

10. The method of claim 1, further comprising storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

Description:Technique for Language disorder screening
Field of the Invention
[0001] The present invention generally relates to system and method for speech analysis, and more particularly relates to a system and method for language disorder diagnosis or screening technique.
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] Screening for language disorders is an important task that can help identify children who may be at risk for language delays or disorders. Screening can be done in a variety of settings, including healthcare clinics, early childhood education programs, and community centres.
[0004] Previous research in the field of language disorder screening has focused on a range of approaches, including standardized assessments, parent questionnaires, and automated screening tools. Standardized assessments involve administering a standardized test to assess a child's language skills, and can provide a comprehensive assessment of a child's language abilities. Parent questionnaires involve asking parents to report on their child's language skills and behaviors, and can provide valuable information on a child's language development and risk for language disorders.
[0005] Various technological solutions (e.g., methods and systems for screening and treatment of infants demonstrating deficits in auditory processing, Computing technologies for diagnosis and therapy of language-related disorders, etc.) for language disorder screening are disclosed in patent literature.
[0006] The WO2015066203A2 (By- Pau-San HARUTA, Charisse Si-Fei HARUTA, Kieran Bing-Fei HARUTA) relates to computing technologies for diagnosis and therapy of language-related disorders. Such technologies enable computer-generated diagnosis and computer-generated therapy delivered over a network to at least one computing device. The diagnosis and therapy are customized for each patient through a comprehensive analysis of the patient's production and reception errors, as obtained from the patient over the network, together with a set of correct responses at each phase of evaluation and therapy.
[0007] The US9320458B2 (By-Teresa Realpe-Bonilla, Naseem Choudhury, April A. Benasich, Cynthia P. Roesler, Jason Nawyn ) relates to a method and apparatus for screening infants at high risk for central auditory processing deficits and then remediating less efficient processing behaviorally using an adaptive training algorithm that gradually increases sensitivity to rapidly occurring stimuli streams.
[0008] The US20190043619A1 (By- Cognoa Inc) relates to the methods and apparatus that can evaluate a subject for a developmental condition or conditions and provide improved sensitivity and specificity for categorical determinations indicating the presence or absence of the developmental condition by isolating hard-to-screen cases as inconclusive. The methods and apparatus disclosed herein can be configured to be tunable to control the tradeoff between coverage and reliability and to adapt to different application settings and can further be specialized to handle different population groups.
[0009] However, the known solutions are expensive, required extensive expertise and non-reliable. Thus, there is need to improvement in this domain.

Summary
[00010] The present invention generally relates to system and method for speech analysis, and more particularly relates to a system and method for language disorder diagnosis or screening technique.
[00011] 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.
[00012] The following paragraphs provide additional support for the claims of the subject application.
[00013] Embodiments of the present disclosure may include a system for language disorder screening, including a user interface for presenting a language screening test to a user. Embodiments may also include a speech recognition module configured to record and transcribe the user's spoken responses to the language screening test. Embodiments may also include a language disorder screening module configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria. Embodiments may also include a feedback module configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.
[00014] In some embodiments, the system may include a database of language disorder screening criteria, which may include measures of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills. In some embodiments, the feedback module may be configured to provide detailed feedback to the user based on their language disorder screening score, including an explanation of the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.
[00015] In some embodiments, the system may include a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information. In some embodiments, the system may include a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.
[00016] In some embodiments, the method may include accessing a database of language disorder screening criteria, which may include measures of fluency, syntax, semantics, pragmatics, or other relevant language skills. Embodiments may also include providing feedback to the user on their language disorder screening score includes providing detailed feedback on the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.
[00017] In some embodiments, the method may include refining the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information. In some embodiments, the method may include storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.
[00018] Embodiments of the present disclosure may also include a method for language disorder screening, including presenting a language screening test to a user via a user interface. Embodiments may also include recording and transcribing the user's spoken responses to the language screening test using a speech recognition module. Embodiments may also include analysing the transcribed responses using a language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria. Embodiments may also include providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.
Brief Description of the Drawings
[00019] 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:
[00020] FIG. 1 is a block diagram illustrating a system for language disorder screening, according to some embodiments of the present disclosure.
[00021] FIG. 2 is a detailed block diagram further illustrating the system (from FIG. 1) for language disorder screening, according to some embodiments of the present disclosure.
[00022] FIG. 3 is a flowchart illustrating a method for language disorder screening, according to some embodiments of the present disclosure.
Detailed Description
[00023] 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.
[00024] 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.
[00025] The present invention generally relates to system and method for speech analysis, and more particularly relates to a system and method for language disorder diagnosis or screening technique.
[00026] FIG. 1 is a block diagram that describes a system 100 for language disorder screening, according to some embodiments of the present disclosure. In some embodiments, the system 100 may include a user interface 110 for presenting a language screening test to a user, a speech recognition module 120 configured to record and transcribe the user's spoken responses to the language screening test, a language disorder screening module 130 configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria, and a feedback module 140 configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.
[00027] In some embodiments, the feedback module 140 may be configured to provide detailed feedback to the user based on their language disorder screening score. In some embodiments, the system 100 may include a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information. In some embodiments, the system 100 may include a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.
[00028] In some embodiments, the system 100 may access a database of language disorder screening criteria, which mayprovide feedback to the user on their language disorder screening score. In some embodiments, the system 100 may Refine the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information. In some embodiments, the system 100Stores and analyses the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.
[00029] FIG. 2 is a detailed block diagram that further describes the system 100 (from FIG. 1) for language disorder screening, according to some embodiments of the present disclosure. In some embodiments, the system 100 may also include a database 250 of language disorder screening criteria. The database 250 may also include measures 252 of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills.
[00030] FIG. 3 is a flowchart that describes a method for language disorder screening, according to some embodiments of the present disclosure. In some embodiments, at 310, the method may include presenting a language screening test to a user via a user interface. At 320, the method may include recording and transcribing the user's spoken responses to the language screening test using a speech recognition module. At 330, the method may include analysing the transcribed responses using the language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria. At 340, the method may include providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.
[00031] The user interface that presents a language screening test to a user is one example of an embodiment of the current disclosure that may be included in a system for screening for language disorders as part of the present disclosure. A voice recognition module that is set up to capture and transcribe the user's spoken replies to the language screening test is another component that may be included in embodiments. The language disorder screening module 130 that is designed to analyse the transcribed replies and create a language disorder screening score based on one or more language disorder screening criteria may also be included in embodiments. The feedback module that is designed to offer feedback to the user on the screening score and propose relevant follow-up activities based on the screening findings may also be included in embodiments.
[00032] Measures of fluency, pitch level, syntax, semantics, pragmatics, or any other relevant language abilities may be included in a database of language disorder screening criteria that may be included in certain implementations of the system. The feedback module may be configured in some embodiments to provide the user with detailed feedback on their language disorder screening score. This feedback may include an explanation of the criteria that were used, a comparison to normative data, and recommendations for further evaluation or treatment.
[00033] The system may, in certain implementations, comprise a machine learning module for the purpose of modifying the language disorder screening criteria based on the results of an analysis of a database containing language disorder screening scores and the diagnostic information associated with them. The system may, in some implementations, include a data management module that is responsible for storing and analysing the language disorder screening scores as well as the diagnostic information associated with them over the course of time in order to identify trends or patterns in the results of the language disorder screening.
[00034] Accessing a database of language disorder screening criteria, which may include measurement of fluency, syntax, semantics, pragmatics, or any other relevant language abilities is one possible step that may be included in certain implementations of the approach. Providing feedback to the user on their language disorder screening score may also be an embodiment. This feedback may include offering specific comments on the criteria that were utilised, a comparison to normative data, and suggestions for further examination or therapy.
[00035] The technique may, in certain implementations, comprise honing the language disorder screening criteria by means of a machine learning module. This is done on the basis of an examination of a database that contains language disorder screening scores and the diagnostic information connected with them. The technique may, in some implementations, include storing and analysing the language disorder screening scores in conjunction with the related diagnostic information over the course of time in order to find patterns or trends in the outcomes of language disorder screening.
[00036] The current disclosure may also comprise a method for screening for language disorders, which may involve delivering a language screening test to a user through a user interface. In certain embodiments, the user's spoken replies to the language screening exam may be recorded and transcribed using a voice recognition module. A language disorder screening score may be generated based on one or more criteria for screening for language disorders by performing an analysis of the transcribed replies using a language disorder screening module. In certain embodiments, feedback on the screening score is provided to the user, and suitable follow-up activities are suggested based on the findings of the screening.
[00037] 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.
[00038] 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).
[00039] 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.
[00040] 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.
[00041] 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 disorder screening, comprising:
a user interface for presenting a language screening test to a user;
a speech recognition module configured to record and transcribe the user's spoken responses to the language screening test;
a language disorder screening module configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria; and
a feedback module configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.

2. The system of claim 1, further comprising a database of language disorder screening criteria, which may include measures of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills.

3. The system of claim 1, wherein the feedback module is configured to provide detailed feedback to the user on their language disorder screening score, including an explanation of the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

4. The system of claim 1, further comprising a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information.

5. The system of claim 1, further comprising a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

6. A method for language disorder screening, comprising:
presenting a language screening test to a user via a user interface;
recording and transcribing the user's spoken responses to the language screening test using a speech recognition module;
analysing the transcribed responses using a language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria;
providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.

7. The method of claim 1, further comprising accessing a database of language disorder screening criteria, which may include measures of fluency, syntax, semantics, pragmatics, or other relevant language skills.

8. The method of claim 1, wherein providing feedback to the user on their language disorder screening score includes providing detailed feedback on the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

9. The method of claim 1, further comprising refining the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information.

10. The method of claim 1, further comprising storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

Technique for Language disorder screening

Abstract
The instant disclosure elucidates a system for screening for language disorders is a user interface that delivers a language screening test to a user. Embodiments may also make use of a voice recognition module configured to record and transcribe the user's spoken responses to the language screening test. Embodiments may additionally include a language disorder screening module that is programmed to analyse the transcribed responses and provide a language disorder screening score based on one or more language disorder screening criteria. In certain implementations, the screening results are shown to the user together with suggestions for next steps depending on the results of the screening.

, Claims:Claims
I/We Claim:
1. A system for language disorder screening, comprising:
a user interface for presenting a language screening test to a user;
a speech recognition module configured to record and transcribe the user's spoken responses to the language screening test;
a language disorder screening module configured to analyse the transcribed responses and generate a language disorder screening score based on one or more language disorder screening criteria; and
a feedback module configured to provide feedback to the user on the screening score and suggest appropriate follow-up actions based on the screening results.

2. The system of claim 1, further comprising a database of language disorder screening criteria, which may include measures of fluency, pitch level, syntax, semantics, pragmatics, or other relevant language skills.

3. The system of claim 1, wherein the feedback module is configured to provide detailed feedback to the user on their language disorder screening score, including an explanation of the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

4. The system of claim 1, further comprising a machine learning module for refining the language disorder screening criteria based on analysis of a database of language disorder screening scores and associated diagnostic information.

5. The system of claim 1, further comprising a data management module for storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.

6. A method for language disorder screening, comprising:
presenting a language screening test to a user via a user interface;
recording and transcribing the user's spoken responses to the language screening test using a speech recognition module;
analysing the transcribed responses using a language disorder screening module to generate a language disorder screening score based on one or more language disorder screening criteria;
providing feedback to the user on the screening score and suggesting appropriate follow-up actions based on the screening results.

7. The method of claim 1, further comprising accessing a database of language disorder screening criteria, which may include measures of fluency, syntax, semantics, pragmatics, or other relevant language skills.

8. The method of claim 1, wherein providing feedback to the user on their language disorder screening score includes providing detailed feedback on the criteria used, a comparison to normative data, and recommendations for further evaluation or treatment.

9. The method of claim 1, further comprising refining the language disorder screening criteria using a machine learning module based on analysis of a database of language disorder screening scores and associated diagnostic information.

10. The method of claim 1, further comprising storing and analysing the language disorder screening scores and associated diagnostic information over time to identify trends or patterns in language disorder screening results.