1. A method of providing a framework for merging a plurality of automatic speech recognition (ASR) systems having a shared deep neural network (DNN) feature transformation, comprising: receiving, by a computing device, at least one utterance; training, by the computing device, a DNN feature transformation with a criterion utilizing the received at least one utterance, the DNN feature transformation comprising a plurality of hidden layers; generating, by the computing device, an output from a top hidden layer in the plurality of hidden layers for the at least one utterance; utilizing, by the computing device, the top hidden layer output to generate a network comprising a bottleneck layer and an output layer; extracting, by the computing device, one or more weights between the top hidden layer and the bottleneck layer, the one or more weights representing a feature dimension reduction; generating, by the computing device, a plurality of scores from a first ASR system and a second ASR system in the plurality of ASR systems; and combining, by the computing device, the plurality of scores from the first ASR system and the second ASR system to merge the plurality of ASR systems, the plurality of ASR systems sharing the DNN feature transformation.