Modeling end to end dialogues using intent oriented decoding

A computer architecture operating on a hardware computing device and configured to predict answers to questions, the computer architecture comprising:

• an intent detector configured to:
• receive a dialogue of questions and answers,
• identify intents in the questions and answers,
• identify one of the questions as a pending question, and
• identify a series of questions and answers preceding the pending question as a conversation;
• an intent transition model configured to generate desired answer intents from the intents;
• an answer prediction model configured to generate answer predictions based on the pending question with intents, the conversation with intents, and the desired answer intents;
• wherein the intent decoder is configured to perform a diverse beam search on the desired answer intents and use results of the diverse beam search to generate the answer predictions.

A computer program stored on a non-transitory storage medium, the computer program comprising a set of instructions that, when executed by a hardware processor, cause the hardware processor to:

• operate an answer prediction model;
• capture a dialog that includes a series of questions and answers;
• input a pending question in the dialog into the answer prediction model;
• input a conversation of questions and answers prior to the pending question into the answer prediction model to capture a context for the pending question;
• and
• use the answer prediction model to generate answer predictions for the pending question;
• wherein the instructions, when executed by the hardware processor, operate an intent detector configured to:
• identify intents in the pending question;
• identify intents in the questions and answers in the conversation;
• input the pending question with intents into the answer prediction model;
• input the conversation with intents into the answer prediction model;
• and
• use the question with intents and the conversation with intents to generate the answer predictions;
• wherein the instructions, when executed by the hardware processor, are further configured to:
• operate an intent transition model;
• combine intents in the dialogue into a conversation intent journey;
• inset the conversation intent journey into the intent transition model to generate desired answer intents;
• input the desire answer intents into the answer prediction model to generate the answer predictions;
• wherein the instructions, when executed by the hardware processor, are further configured to:
• input the pending question with intents into a question encoder in the answer prediction model;
• input the conversation with intents into a conversation encoder in the answer prediction model;
• and
• input the desired answer intents into a decoder in the answer prediction model.

A processing system for operating a dialogue analyzer, the processing system comprising:

• a processing device configured to:
• operate an intent detector;
• operate an answer prediction model;
• capture a dialogue of user questions and agent answers to the user questions;
• use the intent detector to identify question intents in the user questions and answer intents in the agent answers;
• identify a pending question in the dialogue;
• use the intent detector to add intents to the pending question;
• input the pending question with intents into the answer prediction model;
• identify a sequence of questions and answers prior to the pending question as a conversation;
• use the intent detector to add intents to the questions and answers;
• input the conversation with intents into the answer prediction model;
• use the answer prediction model to generate answer predictions for the pending question based on the question with intents and the conversation with intents;
• input the pending question with intents into a question encoder in the answer prediction model;
• input the conversation with intents into a conversation encoder in the answer prediction model;
• and
• input the answer intents into a decoder in the answer prediction model;
• wherein the question encoder generates a question vector and inputs the question vector into the decoder and the conversation encoder generates a conversation vector and inputs the conversation vector into the decoder.

A processing system for operating a dialogue analyzer, the processing system comprising:

• a processing device configured to:
• operate an intent detector;
• operate an answer prediction model;
• capture a dialogue of user questions and agent answers to the user questions;
• use the intent detector to identify question intents in the user questions and answer intents in the agent answers;
• identify a pending question in the dialogue;
• use the intent detector to add intents to the pending question;
• input the pending question with intents into the answer prediction model;
• identify a sequence of questions and answers prior to the pending question as a conversation;
• use the intent detector to add intents to the questions and answers;
• input the conversation with intents into the answer prediction model;
• use the answer prediction model to generate answer predictions for the pending question based on the question with intents and the conversation with intents;
• wherein the processing device is further configured to:
• operate an intent transition model;
• use the intents from the conversation as a conversation intent journey;
• input the conversation intent journey into the intent transition model;
• use the intent transition model to generate desired answer intents from the conversation intent journey;
• input the answer intents into the answer prediction model;
• generate the answer predictions with the answer prediction model based on the desired answer intents;
• perform a diverse beam search on the desired answer intents;
• and
• use results of the diverse beam search in the answer prediction model to generate the answer predictions.

A processing system for operating a dialogue analyzer, the processing system comprising:

• a processing device configured to:
• operate an intent detector;
• operate an answer prediction model;
• capture a dialogue of user questions and agent answers to the user questions;
• use the intent detector to identify question intents in the user questions and answer intents in the agent answers;
• identify a pending question in the dialogue;
• use the intent detector to add intents to the pending question;
• input the pending question with intents into the answer prediction model;
• identify a sequence of questions and answers prior to the pending question as a conversation;
• use the intent detector to add intents to the questions and answers;
• input the conversation with intents into the answer prediction model;
• and
• use the answer prediction model to generate answer predictions for the pending question based on the question with intents and the conversation with intents,
• wherein the processing device is further configured to:
• operate an intent transition model;
• use the intents from the conversation as a conversation intent journey;
• input the conversation intent journey into the intent transition model;
• use the intent transition model to generate desired answer intents from the conversation intent journey;
• input the desired answer intents into the answer prediction model;
• generate the answer predictions with the answer prediction model based on the desired answer intents;
• wherein the processing device is further configured to:
• store training data including dialogues of questions and answers;
• identify intents in the questions and answers in the training data;
• identify a pending question in the training data;
• input the pending question with intents from the training data into a question encoder in the answer prediction model;
• identify a conversation of questions and answers in the training data prior to the pending question;
• input the questions with intents and answers with intents for the conversation from the training data into a conversation encoder in the answer prediction model;
• identify an answer in the training data to the pending question;
• and
• input the answer in the training data to the pending question with intents into a decoder in the answer prediction model.