1. A method, comprising: receiving an acoustic signal at an automatic speech recognition (ASR) system that comprises a deep neural network (DNN), the DNN trained based at least in part upon training data, the training data comprising spoken utterances in a source language, the acoustic signal comprising a spoken utterance that includes a word in a target language; extracting a plurality of features from the acoustic signal to form a feature vector; providing the feature vector to an input layer of the DNN, the DNN producing an output responsive to being provided with the feature vector; and identifying the word in the target language in the spoken utterance based upon the output of the DNN.