Mobile voice recognition data collection and processing

• US 20090030689A1
• Filed: 10/03/2006
• Published: 01/29/2009
• Est. Priority Date: 10/03/2006
• Status: Abandoned Application

• Current Assignee: Accutrak Inventory Specialists LLC
• Original Assignee: Accutrak Inventory Specialists LLC
• Inventors: Wood, Kevin, Perrin, Vincent, Perrin, Judi, Joost, Michael
• Application Number:
  US11/542,028
• Publication Number:
  US 20090030689A1
• Time in Patent Office: Days
• US Class Current: 704/246
• CPC Class Codes: G10L 15/065 Adaptation

Abstract

Voice recognition methods, systems and interfaces are used to collect data and produce databases that are then searched and used to produce reports or electronic filings. The databases are developed using a hierarchically designed command structure and a hierarchy of relational databases for the entry and recognition of voice commands. The invention uses an Adaptive Grammar that allows a very high probability for accurate recognition and a rapid recognition response to be achieved. The invention allows for multiple users and multiple mobile computers to maximize voice recognition capabilities.

Claims

1. A method for populating a main database using voice recognition input based on verbal utterances of a user. The method involves:

a) developing a series of data collection models, each model comprising of a series of navigational commands for populating a selected series of data fields of the main database, and each model represented by an client identifier;

b) creating a predefined database for each model, the predefined database contains rules for each field. The rules may contain specific numbers, series of numbers, words or linkages to the words for each unique field;

c) The invention uses Adaptive Grammar that allows the programmer to change the rules for each field. The programmer can change the rules for a field in the program and make the rule fixed or allow the rule for the particular field to be defined in the field by a supervisor. This feature allows a very high probability for accurate recognition and a rapid recognition response;

d) identifying a specific field and the contents of the field, by comparing the rules of a specific field with voice recognition input. The recognition is based on a field identifying verbal utterance of a specific user;

e) identifying a specific users verbal utterance from multiple user utterances and marking it with a unique identifier in the database;

f) multiple users are connected using multiple concurrent audio interfaces g) recording the verified data entries within the data fields by mapping the voice recognition output generated, based on utterances of the users, to the data fields in the main database using the word mapping database for the selected fields; and

repeating steps d), e), f) and g) until the users finish entering data, thereby populating the main database.

2. The method of claim 1 wherein the models, fields and word mapping databases are developed using a hierarchically organized relational database. The models, fields and word mapping databases are based upon the knowledge contained and the predefined fields in the main database;

the relation organized database contains a plurality of nodes having further related nodes, fields and/or attributes.

3. The method of claim 1 wherein the voice recognition output is mapped to data items in the selected fields using a mapping database that includes or may include numbers, series of numbers, words or linkages to the words for each unique field representing spoken words or numbers for populating data items and by comparing voice recognition input to the keywords or numbers

4. The method of claim 3 where the voice recognition input is compared to the mapping database by:

a) comparing the voice recognition input to the field identifiers and determining the proper field using a sequential order;

b) after the proper field has been determined the voice recognition input is compared to the rules for the predefined field and determined to be acceptable or unacceptable;

c) if the voice recognition was acceptable for the field the utterance is recorded in the database and then repeated to the auditor;

d) the system then proceeds to the next sequential field and requests the auditors input

5. The method of claim 3 where the voice recognition input is compared to the database and determined unacceptable:

a) if the system determines the noise or utterance is background noise the system ignores it and purges it from the voice engine queue;

b) if the utterance is completely inappropriate the system responds “

I do not understand” and

returns the auditor to a starting field c) if the system accepts a wrong voice recognition output the auditor has an opportunity to make a correction

6. The method of claim 5 correcting unacceptable input:

a) if the auditor determines by hearing the systems, voice engines, response that the input was incorrect the auditor says “

correction”

the system will respond “

that the system is in correction mode and all entries will be subtracted”

. If you had entered an incorrect area, product, price or quantity you would negate it from the database by negating the quantity you had entered in the incorrect entry sequence. All entries are stored to provide a true audit trail.

7. The method of claim 5 of hearing the systems voice engine response a) after each auditor'"'"'s voice utterance the system attempts to recognize the utterance and if it does records the utterance in the database in the proper field. The system then echo'"'"'s the recognized utterance back to the auditor. b) If the auditor isn'"'"'t sure the echoed response was correct the auditor says “

repeat”

c) The system then repeats back the last 10 voice utterances. This is not limited to 10 utterances but is a number that was selected for feasibility.

8. A method of claim 1 populating a relational database using a hierarchical structure. This allows for systematic storage and retrieval of data. The data is stored and sorted to facilitate the production of reports requested by customers.

9. A method of claim 8 the data is stored in a main database that allows the data to be sorted:

a) the data is sorted to produce reports and the reports may contain information concerning the location of the product or information, the type of product or information, the price of the product and the quantity of the product;

b) the reports may accumulate locations, types or a combination of instances c) the reports may be customized to meet the clients needs

10. A method of claim 8 the data is stored in a main database and may be retrieved by auditor identification:

a) the data is stored in the exact order it is received and affixed with a time stamp;

b) the data can be sorted in a variety of ways to create a true audit trail that is used to validate the audit;

c) the data can be sorted and printed by auditor, by location or by product

11. A method of claim 1 allowing multiple auditors, users, on the same mobile computing system:

a) the system has the capability of assigning each auditor a data flow channel;

b) the auditors may log in and out during the work flow;

c) the auditors may individually adjust their volume on headsets to allow for noise conditions;

d) the auditor may adjust the speed in which the voice recognition engine responds to their commands e) the system trains a voice recognition profile for each auditor and stores it, the voice recognition profile is continually being upgraded;

f) multiple users are connected using multiple concurrent audio interfaces

12. A method of claim 1 allowing for multiple computers to be networked to:

a) allow for additional auditors to work on a project;

b) allow for the range of the microphones to be extended

13. A method of claim 12 allows the current limitations of computers to be overcome. Voice recognition requires a tremendous amount of computing power and the current invention developed a way to network computers to allow for additional auditors to work on a project.

14. A method of claim 12 allows the invention to overcome the current limitations regarding range of microphones:

a) current microphone technology allows for a limited transmission range, 300 feet maximum;

b) by networking computers the range can be extended.

15. A method of claim 12 that allows the invention to utilize mobile computers for voice recognition:

a) the invention is built to allow the voice recognition system to reside on a mobile computing system;

b) this allows data to be collected and generate reports in the field real time

16. A method of claim 13 allows the invention to run on dual or quad processor computers:

a) by developing the invention as individual units working together it can run the voice recognition system on one core;

b) by identifying each user and what channel they are recording data the invention can break specific users out to run on separate core. Thereby, allowing the invention to run at a maximum performance and with maximum users.

18. A method of claim 1 that allows the database to embed a field with a word or number:

a) this allows for very specific data to be embedded in a field which increases recognition accuracy and the speed of recognition b) this allows the embedded field to be assigned to the previous entry field

19. A method of claim 18 b) allows the invention to assign a price to a particular product or item described in 18 a) when the product or item is recognized and saved in the database the price field would be skipped and the auditor be prompted to count a) this allows for increased accuracy and speed for collecting data