Methods and systems enabling natural language processing, understanding, and generation

1 . A method of establishing or generating multi-turn communications between a robot device and an individual, comprising:

accessing instructions from one or more physical memory devices for execution by one or more processors;

executing instructions accessed from the one or more physical memory devices by the one or more processors;

storing, in at least one of the physical memory devices, signal values resulting from having executed the instructions on the one or more processors;

wherein the accessed instructions are to enhance conversation interaction between the robot device and the individual; and

wherein executing the conversation interaction instructions further comprising:

receiving, from a speech-to-text recognition computing device, one or more input text files associated with the individual's speech;

filtering, via a prohibited speech filter, the one or more input text files to verify the one or more input text files are not associated with prohibited subjects;

analyzing the one or more input text files to determine an intention on the individuals speech;

performing actions on the one or more input text files based at least in part on the analyzed intention;

generating one or more output text files based on the performed actions;

communicating the created one or more output text files to the markup module;

analyzing, by the markup module, the received one or more output text files for sentiment,

based at least in part on the sentiment analysis, associating an emotion indicator, and/or multimodal output actions for the robot device with the one or more output text files:

verifying, by the prohibited speech filter, the one or more output text files do not include prohibited subjects;

analyzing the one or more output text files, the associated emotion indicator and the multimodal output actions to verify conformance with the robot device persona parameters; and

communicating the one or more output text files, the associated emotion indicator and the multimodal output actions to the robot device.

2 . The method of claim 1 , wherein executing the conversation interaction instructions further comprises:

before the one or more input text files are received, filtering, via a dialog manager module in the robot device, the one or more input text files to determine whether social chat modules of the cloud-based computing device should be utilized to process the one or more input text files.

3 . The method of claim 2 , wherein the dialog manager module in the robot device analyzes the one or more input text files to determine if a special command was received, an open question is present, or there is a lack of matching existing conversation patterns on the robot device in order to determine whether or not to communicate the one or more input text files to the social chat modules of the cloud-based computing device.

4 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

wherein if the intent manager module determines that a delay may occur in receiving the one or more output text files, generating delay output text files and/or delay multimodal output action files to mask a delay in response time.

5 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising: if the prohibited speech filter identifies that the one or more input text files are associated with the prohibited subjects, the prohibited speech filter communicating with the knowledge database and the knowledge database communicating one or more safe output text files to the chat module.

6 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

filtering, via a special topics filter, the one or more input text files to determine if the one or more input text files include special topics;

retrieving one or more specialized redirect text files if the special topics filter determines the one or more input text files include the special topics; and

communicating the one or more specialized redirect text files to the markup module for processing.

7 . The method of claim 1 , wherein the special topics include Christmas, holiday or birthday topics.

8 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

if the output persona filter determines the one or more output text files, the associated emotion indicator and the multimodal output actions do not conform with the robot device persona parameters,

searching, by the social chat module, for acceptable output text files, associated emotion indicators, and/or multimodal output actions in a knowledge database and/or the one or memory modules.

9 . The method of claim 8 , wherein executing the conversation interaction instructions further comprising:

If the social chat module locates one or more acceptable output text files, associated emotion indicators, and/or multimodal output actions,

the social chat module communicating the acceptable output text files, associated emotion indicators, and/or multimodal output actions to the robot device.

10 . The method of claim 8 , wherein executing the conversation interaction instructions further comprising:

if the social chat module does not locale one or more acceptable output text files, associated emotion indicators, and/or multimodal output actions,

the social chat module retrieving one or more redirect text files from the knowledge database and/or the one or more memory devices, and

communicating the one or more redirect text files to the markup module for processing.

11 . The method of claim 1 , wherein the one or more output text files from the social chat module are analyzed to determine if words included in the one or more input text files include a question requiring data on an external computing device outside the one or more memory devices; and

the social chat module communicating with a third-party application programming interface to the external computing device to retrieve answer data with respect to the question in the input text files; and

inserting the retrieved answer data in the one or more output text files.

12 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

analyzing, by a context module, the one or more input text files to extract factual contextual text information from the user's speech; and

storing the factual extracted contextual information in the one or more memory modules.

13 . The method of claim 12 , wherein executing the conversation interaction instructions further comprising:

identifying situations where past conversation factual extracted contextual information from the one or more memory modules may be inserted into the generated one or more output text files after the actions have been performed on the one or more input text files.

14 . The method of claim 12 , wherein executing the conversation interaction instructions further comprising:

identifying situations where other factual extracted contextual information from the one or more memory modules may be inserted into the generated one or more output text files after the actions have been performed on the one or more input text files.

15 . The method of claim 12 , wherein executing the conversation interaction instructions further comprising:

eliminating redundant text from the extracted contextual text information to generate relevant contextual text information; and

storing the relevant contextual text information in the one or more memory modules.

16 . The method of claim 1 , wherein the actions performed on the one or more input text files include identifying factual information requested in the one or more input text files;

wherein the actions performed on the one or more input text files include communicating with a third-party application programming interface to obtain the requested factual information from an external computing device or software program; and

wherein the actions performed on the one or more input text files include adding the obtained factual information to the generated one or more output text files communicated to the markup module.

17 . The method of claim 1 , wherein the actions performed on the one or more input text files include identifying factual information requested in the one or more input text files;

wherein the actions performed on the one or more input text files include communicating with a knowledge database and/or the one or more memory modules to obtain the requested factual information; or

wherein the actions performed on the one or more input text files include adding the obtained factual information to the generated one or more output text files communicated to the markup module.

18 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

analyzing, by the markup module, the received one or more output text files for relevant conversational and/or metaphorical aspects; and

based at least in part on the conversational and/or metaphorical analysis associating an emotion indicator and/or multimodal output actions for the robot device with the one or more output text files.

19 . The method of claim 1 , wherein executing the conversation interaction instructions further comprising:

analyzing, by the markup module, the received one or more output text files for contextual information; and

based at least in part on the contextual information analysis, associating an emotion indicator and/or multimodal output actions for the robot device with the one or more output text files.