Abstract:Automatic speech recognition (ASR) systems often have difficulty recognizing long-tail entities such as contact names and local restaurant names, which usually do not occur, or occur infrequently, in the system's training data. In this work, we present a method which uses learned text embeddings and nearest neighbor retrieval within a large database of entity embeddings to correct misrecognitions. Our text embeddings are produced by a neural network trained so that the embeddings of acoustically confusable phr… Show more
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