US 12,468,938 B2
Training example generation to create new intents for chatbots
Paulo Rodrigo Cavalin, Rio de Janeiro (BR); Ana Paula Appel, Sao Paulo (BR); Bruno Silva, Sao Paulo (BR); and Renato Luiz de Freitas Cunha, Sao Paulo (BR)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Sep. 21, 2021, as Appl. No. 17/480,398.
Prior Publication US 2023/0092274 A1, Mar. 23, 2023
Int. Cl. G06N 3/08 (2023.01); G06F 16/2455 (2019.01); G06N 3/006 (2023.01); G06N 3/042 (2023.01)
CPC G06N 3/08 (2013.01) [G06F 16/2455 (2019.01); G06N 3/006 (2013.01); G06N 3/042 (2023.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving a topic for building a new intent on which to train a chatbot;
mapping the received topic to meta-knowledge based on similarity of the topic and the meta-knowledge;
searching a database of chatbot training data for a candidate intent having the meta-knowledge;
extracting utterances associated with the candidate intent; and
inputting the received topic and the extracted utterances to a trained machine learning model, the trained machine learning model generating example utterances for the new intent, the trained machine learning model having been trained to convert a first intent to a second intent based on: a plurality of pairs of input samples, a pair of input sample in the plurality of pairs of input samples comprising a training utterance and a training utterance's meta-knowledge associated with the first intent, and using as ground truth a plurality of second intent's examples and associated meta-knowledge;
discarding an example utterance from the generated example utterances responsive to determining that the example utterance is similar, based on a threshold level of similarity, to an extracted utterance of the extracted utterances used as input in training the machine learning model;
presenting via a graphical user interface the at least the example utterances for validation of the example utterances;
training the chatbot using at least the example utterances without the discarded example utterance, generated by the trained machine learning model; and
automatically updating knowledge and retraining of the chatbot using a set of intents that includes the first intent and the converted second intent thereby causing the chatbot to interact with a user by carrying on a conversation associated with the new intent that is different from a previous intent.