Submodular Rank Aggregation on Score-based Permutations for Distributed Automatic Speech Recognition

27 Jan 2020 Jun Qi Chao-Han Huck Yang Javier Tejedor

Distributed automatic speech recognition (ASR) requires to aggregate outputs of distributed deep neural network (DNN)-based models. This work studies the use of submodular functions to design a rank aggregation on score-based permutations, which can be used for distributed ASR systems in both supervised and unsupervised modes... (read more)

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