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A segmental framework for fully-unsupervised large-vocabulary speech recognition
We also show that the discovered clusters can be made less speaker- and gender-specific by using an unsupervised autoencoder-like feature extractor to learn better frame-level features (prior to embedding).
LANGUAGE MODELLING LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION SPEECH RECOGNITION UNSUPERVISED SPEECH RECOGNITION