METHOD AND APPARATUS FOR AUTOMATIC INTENT DETECTION IN CUSTOMER SERVICE ENVIRONMENTS
Method and apparatus for intent detection in customer service environments includes a processor, and a memory storing instructions that, when executed by the processor, configure the apparatus to perform a method. The method includes processing an input includes a message of a conversation by multiple artificial intelligence/machine learning (AI/ML) models. The message includes a transcript or a summary of at least a part of the conversation. Each of the multiple models is configured to generate, based on the input, an output including an intent of the conversation. A single output corresponding to the conversation is determined based on the multiple outputs, one from each of the multiple models.
1 . A computing apparatus for automatic intent detection, the computing apparatus comprising:
a processor; and
a memory storing instructions that, when executed by the processor, configure the apparatus to:
process an input comprising a message of a conversation by a plurality of artificial intelligence/machine learning (AI/ML) models, each of the plurality of models configured to generate an output comprising an intent of the conversation from the input, the message comprising at least one of a transcript of at least a part of the conversation, or a summary of the at least a part of the conversation;
receive a plurality of outputs, one from each of the plurality of models, each of the plurality of outputs comprising an intent of the conversation; and
determine, from the plurality of outputs, a single output of the conversation.
2 . The computing apparatus of claim 1 , wherein the determining comprises:
generating, from the plurality of outputs, a plurality of clusters of the outputs, each of the plurality of clusters having the same value of the intent;
identifying the cluster with the highest number of outputs; and
selecting the intent of the identified cluster as the single output.
3 . The computing apparatus of claim 1 , wherein the determining comprises:
ranking at least two outputs from the plurality of outputs on a confidence measure of each of the plurality of outputs; and
selecting, from the plurality of outputs, the output with the highest confidence measure as the single output.
4 . The computing apparatus of claim 1 , wherein the receiving comprises waiting for the output from each of the plurality of models.
5 . The computing apparatus of claim 1 , wherein the receiving comprises waiting for a cutoff time threshold, and wherein-the determining comprises determining the single output from the outputs received within the cutoff time threshold.
6 . The computing apparatus of claim 5 , wherein the cutoff time threshold is 1,500 ms.
7 . A computer-implemented method for automatic intent detection, the method comprising:
processing an input comprising a message of a conversation by a plurality of artificial intelligence/machine learning (AI/ML) models, each of the plurality of models configured to generate an output comprising an intent of the conversation from the input, the message comprising at least one of a transcript of at least a part of the conversation, or a summary of the at least a part of the conversation;
receiving a plurality of outputs, one from each of the plurality of models, each of the plurality of outputs comprising an intent of the conversation; and
determining, from the plurality of outputs, a single output of the conversation.
8 . The computer-implemented method of claim 7 , wherein the determining comprises:
generating, from the plurality of outputs, a plurality of clusters of the outputs, each of the plurality of clusters having the same value of the intent;
identifying the cluster with the highest number of outputs; and
selecting the intent of the identified cluster as the single output.
9 . The computer-implemented method of claim 7 , wherein the determining comprises:
ranking at least two outputs from the plurality of outputs on a confidence measure of each of the plurality of outputs; and
selecting, from the plurality of outputs, the output with the highest confidence measure as the single output.
10 . The computer-implemented method of claim 7 , wherein the receiving comprises waiting for the output from each of the plurality of models.
11 . The computer-implemented method of claim 7 , wherein the receiving comprises waiting for a cutoff time threshold, and wherein-the determining comprises determining the single output from the outputs received within the cutoff time threshold.
12 . The computer-implemented method of claim 11 , wherein the predefined cutoff time threshold is 1,500 ms.
13 . A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:
process an input comprising a message of a conversation by a plurality of artificial intelligence/machine learning (AI/ML) models, each of the plurality of models configured to generate an output comprising an intent of the conversation from the input, the message comprising at least one of a transcript of at least a part of the conversation, or a summary of the at least a part of the conversation;
receive a plurality of outputs, one from each of the plurality of models, each of the plurality of outputs comprising an intent of the conversation; and
determine, from the plurality of outputs, a single output of the conversation.
14 . The computer-readable storage medium of claim 13 , wherein the determining comprises:
generate, from the plurality of outputs, a plurality of clusters of the outputs, each of the plurality of clusters having the same value of the intent;
identify the cluster with the highest number of outputs; and
select the intent of the identified cluster as the single output.
15 . The computer-readable storage medium of claim 13 , wherein the determining comprises:
rank at least two outputs from the plurality of outputs on a confidence measure of each of the plurality of outputs; and
select, from the plurality of outputs, the output with the highest confidence measure as the single output.
16 . The computer-readable storage medium of claim 13 , wherein the receiving comprises wait for the output from each of the plurality of models.
17 . The computer-readable storage medium of claim 13 , wherein the receiving comprises wait for a cutoff time threshold, and wherein-the determining comprises determining the single output from the outputs received within the cutoff time threshold.
18 . The computer-readable storage medium of claim 17 , wherein the predefined cutoff time threshold is 1,500 ms.