Method for conversion and classification of data based on context
When a new communication is received at a server, the system can generate machine readable data pertaining to the communication, e.g., a transcript for the communication. Using the transcript, the system can utilize natural language processing techniques to find at least one request in the communication. The system can search summaries of prior communications, and if there is a communication including a similar request, the system can display a record of the prior communication.
1. A method comprising:
receiving a first phone call;
transcribing the first phone call to create a first transcript;
performing a natural language processing technique to determine a first discussion attribute of the first transcript;
associating the first transcript with a first discussion attribute label selected from a group of labels including a plurality of discussion attribute labels;
receiving a second phone call;
transcribing the second phone call to create a second transcript;
performing the natural language processing technique to determine a second discussion attribute of the second call;
associating the second transcript with a second discussion attribute label selected from the group of labels;
comparing the first discussion attribute label to the second discussion attribute label;
in response to a determination that the first discussion attribute label matches the second discussion attribute label, displaying a report of the first transcript to a recipient of the second call, wherein the report of the first transcript includes a summary of the first transcript;
searching a database including a plurality of transcripts, each transcript being associated with at least one discussion attribute label, wherein during the search, the second discussion attribute label is compared to the discussion attribute label of each of a subset of the plurality of transcripts;
selecting at least one of the plurality of transcripts which is associated with the discussion attribute label that matches the second discussion attribute label;
combining the report of the first transcript with a report of a selected transcript to create a combined report; and
displaying the combined report to the user.
2. The method of claim 1 , further comprising:
performing the natural language processing technique to determine a third discussion attribute of the second call;
associating the second transcript with a third discussion attribute label selected from the group of labels;
searching the database, wherein during the search, the third discussion attribute label is compared to the discussion attribute label of the plurality of transcripts;
in response to a determination that the discussion attribute label of one of the plurality of transcripts matches the third discussion attribute label, displaying a report of the one of the plurality of transcripts to the recipient of the second call.
3. The method of claim 1 , further comprising:
performing the natural language processing technique to determine another discussion attribute of the second call;
if the other discussion attribute of the second call matches the second discussion attribute of the second call, continue displaying the report of the first transcript to the recipient of the second call;
if the other discussion attribute of the second call does not match the second discussion attribute of the second call:
associating the second transcript with the other discussion attribute label selected from the group of labels;
searching the database, wherein during the search, the other discussion attribute label is compared to the discussion attribute label of the plurality of transcripts;
in response to a determination that the discussion attribute label of one of the plurality of transcripts matches the other discussion attribute label, display a report of the one of the plurality of transcripts to the recipient of the second call instead of the report of the first transcript.
4. The method of claim 1 , wherein the combined report includes a problem statement from the first transcript and a problem statement from the selected transcript.
5. The method of claim 4 , further comprising:
displaying a feedback prompt to the user regarding a quality of the combined report.
6. The method of claim 5 , further comprising:
storing the feedback in a database including a plurality of feedbacks relating to combined reports.
7. The method of claim 6 , further comprising:
training the machine learning model using the plurality of feedbacks as training data.
8. The method of claim 1 , wherein the combined report includes the summary from the first transcript and a summary from the selected transcript.
9. The method of claim 1 , wherein the combined report includes a duration from the first transcript and a duration from the selected transcript.
10. The method of claim 1 , wherein the combined report includes an identity of a caller from the first transcript and an identity of a caller from the selected transcript.
11. The method of claim 1 , wherein the natural language processing technique uses a machine learning model.
12. The method of claim 1 , wherein the first discussion attribute is a statement of a problem.
13. The method of claim 1 , wherein the report of the first transcript includes a duration of the call.
14. The method of claim 1 , wherein the report of the first transcript includes an identity of a participant in the call.
15. The method of claim 1 , wherein the report of the first transcript includes a statement of the problem.
16. The method of claim 1 , wherein a plurality of discussion attributes are associated with the first discussion attribute label.