I-Vector Based Clustering Training Data in Speech Recognition

摘要

Methods and systems for i-vector based clustering training data in speech recognition are described. An i-vector may be extracted from a speech segment of a speech training data to represent acoustic information. The extracted i-vectors from the speech training data may be clustered into multiple clusters using a hierarchical divisive clustering algorithm. Using a cluster of the multiple clusters, an acoustic model may be trained. This trained acoustic model may be used in speech recognition.

主权项

1. A computer-implemented method for clustering training data in speech recognition, the method comprising:
extracting a plurality of i-vectors from speech data including a plurality of speech segments; clustering the plurality of i-vectors into a plurality of clusters; training an acoustic model using one of the plurality of clusters; and recognizing one or more other speech segments using the trained acoustic model.