Systems and methods for parsing and correlating solicitation video content

1. A system for parsing and correlating solicitation video content, the system comprising a computing device configured to:

receive a solicitation video related to a subject, wherein the solicitation video comprises:

at least an image component; and

at least an audio component, wherein the audio component includes audible verbal content related to at least an attribute of the subject;

transcribe at least a keyword as a function of the at least an audio component using an automatic speech recognition process including dynamic time warp-based speech recognition;

extract at least a feature as a function of the at least an image component through an audio visual speech recognition process, wherein the at least a feature comprises at least a representation of an object;

associate the subject with at least a job description as a function of the at least a keyword and the at least a feature; and

calculate a ranking of the subject out of a plurality of candidates, wherein the ranking is based on a description-centric ranking factor.

2. The system of claim 1 , wherein associating the subject with the job description further comprises classifying, using at least a candidate classifier, the subject to the at least a job description.

3. The system of claim 1 , wherein transcribing the at least a keyword further comprises using a fuzzy logic comparison.

4. The system of claim 1 , further comprising determining a relevance as a function of the association between the subject and the at least a job description.

5. The system of claim 1 , wherein extracting the at least a feature comprises performing pose-estimation.

6. The system of claim 5 , wherein one or more of recognizing the at least a feature and associating the subject with the at least a job description as a function of the at least a feature uses a machine-learning process.

7. The system of claim 1 , wherein one or more of transcribing the at least a keyword and associating the subject with the at least a job description as a function of the at least a keyword uses a machine-learning process.

8. The system of claim 1 , wherein the at least an image component includes visual verbal content; and the computing device is further configured to:

recognize at least a keyword as a function of the visual verbal content; and

associate the subject with the at least a job description as a function of the at least a keyword.

9. The system of claim 1 , wherein transcribing the at least a keyword comprises natural language processing.

10. The system of claim 1 , wherein the at least an audio component includes audible non-verbal content related to at least an attribute of the subject; and the computing device is further configured to:

recognize at least a feature as a function of the audible non-verbal content; and

associate the subject with the at least a job description as a function of the at least a feature.

11. A method of parsing and correlating solicitation video content, the method comprising:

receiving, using a computing device, a solicitation video related to a subject, wherein the solicitation video comprises:

at least an image component; and

at least an audio component, wherein the audio component includes audible verbal content related to at least an attribute of the subject;

transcribing, using the computing device, at least a keyword as a function of the at least an audio component using an automatic speech recognition process including dynamic time warp-based speech recognition;

extracting, using the computing device, at least a feature as a function of the at least an image component through an audio visual speech recognition process, wherein the at least a feature comprises at least a representation of an object;

associating, using the computing device, the subject with at least a job description as a function of the at least a keyword and the at least a feature; and

calculating, using the computing device, a ranking of the subject out of a plurality of candidates, wherein the ranking is based on a description-centric ranking factor.

12. The method of claim 11 , wherein associating the subject with the job description further comprises:

classifying, using the computing device and at least a candidate classifier, the subject to the at least a job description.

13. The method of claim 11 , wherein transcribing the at least a keyword further comprises using a fuzzy logic comparison.

14. The method of claim 11 , further comprising determining a relevance as a function of the association between the subject and the at least a job description.

15. The method of claim 11 , wherein extracting the at least a feature comprises performing pose-estimation.

16. The method of claim 15 , wherein one or more of recognizing the at least a feature and associating the subject with the at least a job description as a function of the at least a feature uses a machine-learning process.

17. The method of claim 11 , wherein one or more of transcribing the at least a keyword and associating the subject with the at least a job description as a function of the at least a keyword uses a machine-learning process.

18. The method of claim 11 , wherein the at least an image component includes visual verbal content; and the method further comprises:

recognizing, using the computing device, at least a keyword as a function of the visual verbal content; and

associating, using the computing device, the subject with the at least a job description as a function of the at least a keyword.

19. The method of claim 11 , wherein transcribing the at least a keyword comprises natural language processing.

20. The method of claim 11 , wherein the at least an audio component includes audible non-verbal content related to at least an attribute of the subject; and the method further comprises:

recognizing, using the computing device, at least a feature as a function of the audible non-verbal content; and

associating, using the computing device, the subject with the at least a job description as a function of the at least a feature.