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Abstract

Certain aspects of the present disclosure provide techniques and apparatus for training and inferencing using a multi-domain machine learning model. An example method generally includes extracting, using a first neural network block, a plurality of features associated with inputs in a multi-domain input data set. A confusion matrix is generated based on the extracted plurality of features. A plurality of clusters is identified from the confusion matrix. Each cluster in the plurality of clusters generally corresponds to one or more data domains in the multi-domain input data set. A first gating neural network is trained based on the multi-domain input data set and the identified plurality of clusters. A plurality of second neural network blocks is trained based on a division of the multi-domain input data set into data associated with each cluster of the plurality of clusters.

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