Voice application platform

• US 10,235,999 B1
• Filed: 06/05/2018
• Issued: 03/19/2019
• Est. Priority Date: 06/05/2018
• Status: Active Grant

• Current Assignee: Voicify, LLC
• Original Assignee: Voicify, LLC
• Inventors: Naughton, Robert T., Laidlaw, Nicholas G., Dunn, Alexander M., McMahon, Jeffrey K.
• Primary Examiner(s): Guerra-Erazo, Edgar X
• Application Number:
  US16/000,798
• Time in Patent Office: 287 Days
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/9038 Presentation of query results
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/28 Constructional details of speech recognition systems
• CPC Class Codes: G10L 2015/221 Announcement of recognition results
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command
• CPC Class Codes: G10L 2015/225 Feedback of the input speech

Abstract

Among other things, requests are received from voice assistant devices expressed in accordance with different corresponding protocols of one or more voice assistant frameworks. Each of the requests represents a voiced input by a user to the corresponding voice assistant device. The received requests are re-expressed in accordance with a common request protocol. Based on the received requests, responses to the requests are expressed in accordance with a common response protocol. Each of the responses is re-expressed according to a protocol of the framework with respect to which the corresponding request was expressed. The responses are sent to the voice assistant devices for presentation to the users.

Claims

1. A computer-implemented method comprising

maintaining a graph of nodes and edges, the graph including (a) nodes representing different types of request elements of requests for service from voice assistant devices, the different types of request elements being associated with different respective voice assistant frameworks, and (b) nodes representing different predefined stored executable processes to be executed to generate responses to respective types of requests for service in accordance with the different voice assistant frameworks with which they are associated,

the maintaining of the graph including updating the graph using outputs of a machine learning algorithm, the updating including adding nodes, updating the positions of nodes, and updating for new and updated types of message elements associated with different voice assistant frameworks,

receiving through a communication network from voice assistant devices that conform to one or more different voice assistant frameworks, requests for service based on speech of end-users, each of the requests for service including a type of request element associated with a corresponding one of the different voice assistant frameworks, each of the requests for service being associated with two or more of the different predefined stored executable processes,

using each of the requests for service and the type of request elements identified from each of the requests for service to traverse the graph of nodes and edges beginning at a node associated with the corresponding one of the voice assistant frameworks to which the request for service conforms and ending at one node matching the type of request element of the request for service, the matching node comprising a predefined stored executable process to be executed to generate a response to the request for service,

executing the predefined stored executable process to generate the response, and

sending the response through the communication network to a corresponding one of the voice assistant devices to cause the corresponding one of the voice assistant devices to respond to the corresponding end user.

2. The method of claim 1 in which the voice assistant devices from which the requests are received conform to two or more different voice assistant frameworks.

3. The method of claim 1 comprising deriving the data from the requests for service by abstracting information in the requests to a data format that is common across the two or more different voice assistant frameworks.

4. The method of claim 1 comprising updating nodes of the graph using outputs of a machine learning algorithm.

5. The method of claim 1 in which information about the requests is used to identify an initial node of the graph at which to begin the traversal.

6. The method of claim 5 comprising automatically adding a node to the graph to serve as the initial node of the graph at which to begin the traversal with respect to requests that conform to an additional voice assistant framework.