Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching | Chih-Kuan Yeh

We consider the problem of training speech recognition systems without using any labeled data, under the assumption that the learner can only access to the input utterances and a phoneme language model estimated from a non-overlapping corpus.