State Farm Mutual Automobile Insurance Company

State Farm Insurance

Duane Lee Marzinzik

Brian Mark Fields

Benjamin F Bowne

Matthew Eric Riley, Sr

J Lynn Wilson

David W Thurber

Nicholas R Baker

Bryan T Wilkerson

Nick U Christopulos

Eric R Moore

Gregory Dwayne Carter

Richard J Lovings

Matthew Aaron Mifflin

Jufeng “James” Peng

Harsh Lalwani

Padmaja Uppaluri

Ryan Jewell

Kevin William Payne

Nicholas U Christopulos

Jufeng James Peng

Lynn M Wilson

Nick Baker

Eric Riley

Todd Wilkerson

Dave Thurber

James Peng

Sunish Menon

Dustin Charles Schneider

Scott Thomas Christensen

Nick Christopoulos

Lynn Wilson

A system for parsing separate intents in natural language speech configured to (i) receive, from the user computer device, a verbal statement of the user including a plurality of words; (ii) translate the verbal statement into text; (iii) label each of the plurality of words in the verbal statement; (iv) detect one or more potential splits in the verbal statement; (v) divide the verbal statement into a plurality of intents based upon the one or more potential splits; and (vi) generate a response based upon the plurality of intents.

Systems and methods for parsing multiple intents in natural language speech

A method for identifying entities may include, during a voice communication with a caller via a caller device, sending to the caller device a first voice prompt that asks the caller to identify a particular entity, receiving from the caller device caller input data indicative of a voice response of the caller, and analyzing the caller input data to determine a set of words spoken by the caller. The method may also include, for each segment of two or more segments of the set of words, determining a level of string matching between the segment and a corresponding segment in a record stored in a database, determining, and based upon the levels of string matching, a level of match certainty for the particular entity from among at least three possible levels of match certainty, and/or selecting, based upon the level of match certainty, a pathway of the algorithmic dialog.

Fuzzy matching for intelligent voice interface

A method provides identification of relevant caller dialog with an intelligent voice interface configured to lead callers through pathways of an algorithmic dialog including available voice prompts. The method may include, during a voice communication with a caller, receiving from the caller device caller input data indicative of a voice input of the caller, and determining, by processing the caller input data, that a first portion of the voice input is intended to convey caller information to the intelligent voice interface, and that a second portion of the voice input is not intended to convey caller information. The method may also include identifying relevant caller information by analyzing the first portion of the voice input without the second portion of the voice input, and storing the relevant caller information in a database and/or selecting a pathway through the algorithmic dialog based upon the relevant caller information.

Audio handler for intelligent voice interface

A method for responding to inferred caller states during dialog with an intelligent voice interface configured to lead callers through pathways of an algorithmic dialog may include, during a voice communication with a caller via a caller device, receiving from the caller device caller input data indicative of a voice input of the caller, and determining, by processing the caller input data, an inferred state of the caller. Determining the inferred state of the caller may include analyzing one or more characteristics, other than textual content, of the voice input. The method may also include selecting a pathway through the algorithmic dialog based upon the inferred state of the caller.

Emotionally aware intelligent voice interface

A method for facilitating reviews of caller interactions with an intelligent voice interface may include receiving raw voice data representing dialog between one or more callers and the intelligent voice interface during one or more respective voice calls, determining, by processing text translation of the raw voice data using one or more natural language processing models, one or more intents of the one or more callers during the one or more voice calls, generating one or more event labels indicative of one or more events associated with the one or more voice calls, and causing a user interface to be presented on a display device. The user interface may enable a user to (i) listen to the raw voice data, (ii) view the one or more intents, and/or (iii) view the one or more event labels.

Call review tool for intelligent voice interface

In a method for handling out-of-sequence caller dialog, an intelligent voice interface is configured to lead callers through pathways of an algorithmic dialog that includes available voice prompts for requesting different types of caller information. The method may include, during a voice communication with a caller via a caller device, receiving from the caller device caller input data indicative of a voice input of the caller, without having first provided to the caller device any voice prompt that requests a first type of caller information, and determining, by processing the caller input data, that the voice input includes caller information of the first type. The method also includes after determining that the voice input includes the caller information of the first type, bypassing one or more voice prompts, of the available voice prompts, that request the first type of caller information.

Intelligent voice interface for handling out-of-context dialog

A method and computer system executes a home loss prevention simulation to provide a user with information on home loss prevention. The method and system may allow the user to select and place one or more home sensors on items and/or in locations within a simulated home environment. Once the user has finished selecting and placing the home sensors in the simulated home, the method and system may begin the home loss prevention simulation by applying different loss-related simulation scenarios to the simulated home. Based the different loss-related scenarios, the method and system may evaluate the placement of the home sensors in the simulated home to determine one or more losses (e.g., fire, water or burglary) and any associated financial costs. At the end of the simulation, the method and system may provide instructional information regarding the simulation results in order to educate the user on how to improve or optimize home loss prevention.

Systems and methods for simulating home loss prevention

A system and method for determining a vehicle insurance premium for a period of time based at least in part on collected vehicle operation data, the system comprising: a mobile device, comprising: one or more sensors associated with the mobile device and configured to automatically collect vehicle operation data during a data collection session; a processor; a non-transitory storage medium; a display; a transmitter; and a set of computer readable instructions stored in the non-transitory storage medium and when executed by the processor configured to allow the mobile device to collect vehicle operation data and transmit the collected vehicle operation data; and a remote processing computer, comprising: a server that receives collected vehicle operation data; a database that stores collected vehicle operation data; and a rating engine that determines a vehicle insurance premium based at least in part on collected vehicle operation data.

Systems and methods using a mobile device to collect data for insurance premiums

A method for providing vehicle operation data to a remote computer or server for calculation of a vehicle insurance premium for a period of time based at least in part on collected vehicle operation data, wherein the method includes steps of: collecting vehicle operation data via a mobile device while the mobile device is associated with an operating vehicle, wherein the vehicle operation data has insurance risk predictive power; and transmitting the collected vehicle operation data from the mobile device to a remote computer. The remote computer or server receives collected vehicle operation data, stores the collected vehicle operation data in a database, a determines a vehicle insurance premium via a rating engine based at least in part on collected vehicle operation data.

Methods using a mobile device to provide data for insurance premiums to a remote computer

A method for determining a vehicle insurance premium for a period of time based at least in part on collected vehicle operation data, wherein a remote computer receives the collected vehicle operation data from a mobile device and calculates an insurance premium based at least in part on the collected vehicle operation data. A method for determining a vehicle insurance premium for a period of time based at least in part on collected vehicle operation data, wherein a server receives collected vehicle operation data, a database stores the collected vehicle operation data, and a rating engine determines a vehicle insurance premium based at least in part on collected vehicle operation data.

Methods to determine a vehicle insurance premium based on vehicle operation data collected via a mobile device

System and methods for simulating home loss prevention

Growing community of inventors

Springfield, IL, United States of America

Duane Lee Marzinzik