Persisting an AI-supported conversation across multiple channels
A method and computing platform to imitate human conversational response as a context transitions across multiple channels (e.g., chat, messaging, email, voice, third party communication, etc.) where inputs to the system are categorized into identified speech acts and physical acts, and a conversational bot is associated to the channels. In this approach, a data model associated with a multi-turn conversation is provided. The data model comprises an observation history, wherein an observation in the observation history includes an identification of a channel in which the observation originates. As turns are added to the multi-turn conversation, a conversational context across multiple channels is persisted using the data model. Using this approach, an AI-supported conversation started in one channel can move to another conversation channel while maintaining the context of the conversation intact and coherent.
1 . A method for imitating a human conversational response across multiple channels, comprising:
associating a multi-turn conversational bot with one or more of the multiple channels;
providing a data model associated with a multi-turn conversation via the multi-turn conversational bot, the data model comprising an observation history, wherein an observation in the observation history includes an identification of a channel in which the observation originates; and
as one or more turns are added to the multi-turn conversation, persisting a conversational context across multiple channels using the data model, wherein persisting the conversational context includes:
setting a value of an attribute during a first turn of the multi-turn conversation that occurs in a first channel; and
using the value during a second turn of the multi-turn conversation that occurs in a second channel that is distinct from the first channel;
wherein the value is used during the second turn automatically and without prompting for re-entry of the value.
2 . The method as described in claim 1 wherein persisting the conversational context includes transitioning the multi-turn conversation from at least the first channel to the second channel.
3 . The method as described in claim 2 wherein the channels are one of: chat, messaging, email, voice, and a communication initiated by a third party.
4 . The method as described in claim 1 wherein the conversational context is maintained in a data object.
5 . The method as described in claim 1 wherein respective turns in the multi-turn conversation are associated with distinct end user sessions.
6 . The method as described in claim 2 wherein the multi-turn conversation transitions from the first channel to the second channel in response to an action initiated by the end user or as a result of activity associated with a process.
7 . The method as described in claim 1 further including controlling the conversational bot to adapt an interaction with a user during a particular turn of the multi-turn conversation based on identification of the channel.
8 . The method as described in claim 1 wherein the multi-turn conversation is associated with a particular end user.
9 . The method as described in claim 1 wherein providing the data model further includes:
receiving an input that includes an attribute; and
responsive to receipt of the input, retrieving the data model from a set of saved data models when a value of the attribute is recognized as being present in the data model.
10 . The method as described in claim 1 wherein the multi-turn conversation is associated with a conversation initiated between a first and second human end user.
11 . A software-as-a-service computing platform, comprising:
computing hardware;
computer software executing on the computer hardware, the computer software comprising computer program instructions executed on the computing hardware and configured to imitate a human conversational response across multiple channels, the computer program instructions configured to:
associate a multi-turn conversational bot with one or more of the multiple channels;
provide a data model associated with a multi-turn conversation, the data model comprising an observation history, wherein an observation in the observation history includes an identification of a channel in which the observation originates; and
as one or more turns are added to the multi-turn conversation, persist a conversational context across multiple channels using the data model, wherein persisting the conversational context includes:
setting a value of an attribute during a first turn of the multi-turn conversation that occurs in a first channel; and
using the value during a second turn of the multi-turn conversation that occurs in a second channel that is distinct from the first channel;
wherein the value is used during the second turn automatically and without prompting for re-entry of the value.
12 . The computing platform as described in claim 11 wherein computer program instructions that persist the conversational context further include computer program instructions configured to transition the multi-turn conversation from at least the first channel to the second channel.
13 . The computing platform as described in claim 12 wherein the set of input and output channels are one of: chat, messaging, email, voice, and a communication initiated by a third party.
14 . The computing platform as described in claim 12 wherein the conversational context is maintained in a data object.
15 . The computing platform as described in claim 11 wherein respective turns in the multi-turn conversation are associated with distinct end user sessions.
16 . The computing platform as described in claim 12 wherein the multi-turn conversation transitions from the first channel to the second channel in response to an action initiated by the end user or as a result of activity associated with a process.
17 . The computing platform as described in claim 11 wherein the computer program instructions further include computer program instructions configured to control the conversational bot to adapt an interaction with a user during a particular turn of the multi-turn conversation based on identification of the channel.
18 . The computing platform as described in claim 11 wherein the multi-turn conversation is associated with a particular end user.
19 . The computing platform as described in claim 11 wherein the computer program instructions configured to provide the data model further include computer program instructions configured to:
receive an input that includes an attribute; and
responsive to receipt of the input, retrieve the data model from a set of saved data models when a value of the attribute is recognized as being present in the data model.