Abstract: The present disclosure relates to a system, a method, and a product for intent discovery. The system includes a processor in communication with a memory storing instructions. When the processor executes the instructions, the instructions are configured to cause the processor to: obtain documents comprising a set of utterances, extract the set of utterances from the documents, generate a set of utterance embeddings based on the set of utterances, clusterize the set of utterance embeddings to obtain a plurality of clusters, obtain a cluster label for each cluster, encode each document based on a number of times each utterance cluster identifier (ID) appears to obtain an encoded document, perform latent Dirichlet allocation (LDA) on the encoded documents to obtain K topics, and each topic corresponding to a list of key clusters with cluster IDs, and for each topic, replace the cluster IDs with the cluster labels.

Abstract: This disclosure relates to systems and methods for discovering intents from multimedia conversations. In an implementation, the system may obtain an optimal parameter configuration based on a topic relevance quantifier. The system may extract topics from the audio calls based on the optimal parameter configuration. The system may determine respective context metrics for each of the topics. The system may select a relevant topic with respect to the intent discovery from the extracted topic based on the respective context metrics. The system may obtain documents associated with the relevant topic from the corpus of documents. The system may display information of the documents associated with the relevant topic via a user interface. The system may receive a feedback data with respect to the relevant topic. The system may determine intent information associated with the relevant topic based on the feedback data.

Abstract: This disclosure relates to systems and methods for discovering intents from multimedia conversations. In an implementation, the system may obtain an optimal parameter configuration based on a topic relevance quantifier. The system may extract topics from the audio calls based on the optimal parameter configuration. The system may determine respective context metrics for each of the topics. The system may select a relevant topic with respect to the intent discovery from the extracted topic based on the respective context metrics. The system may obtain documents associated with the relevant topic from the corpus of documents. The system may display information of the documents associated with the relevant topic via a user interface. The system may receive a feedback data with respect to the relevant topic. The system may determine intent information associated with the relevant topic based on the feedback data.