| CPC G06F 40/35 (2020.01) [G06F 40/279 (2020.01)] | 20 Claims |
|
1. A method comprising:
receiving text including an utterance;
generating a semantic embedding of the utterance using an embedding network;
generating a plurality of feature vectors based on the semantic embedding using a convolution network;
identifying a first plurality of latent codes respectively corresponding to the plurality of feature vectors by identifying a closest latent code from a second plurality of latent codes of a codebook to each corresponding feature vector of the plurality of feature vectors, wherein the second plurality of latent codes of the codebook discretizes a semantic space based on a number of dimensions of the semantic space, and wherein the closest latent code is identified by computing a similarity between the closest latent code and the corresponding feature vector;
identifying a prominent code among the first plurality of latent codes; and
generating an indication that the utterance is a summary utterance based on the prominent code.
|