Maximum likelihood clustering of Gaussians for speech recognition

On the parallel complexity of hierarchical clustering and CC‐complete problems

“…Oftentimes, some sort of hybrid algorithm is developed for a particular application. Real-world applications of hierarchical clustering can be found in the following references: speech recognition [14], web mining [15], lung cancer research [16], and document mining [17]. A wide variety of techniques are presented in these papers.…”

Discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition

“…Top-down decision tree clustering [6] is a sequential algorithm that is often used for context-dependent acoustic modeling on LVCSR tasks. The algorithm uses a tree structure to represent the current status of clustering, and each node in the tree represents a set of acoustic contexts and their corresponding training data.…”

High-accuracy large-vocabulary speech recognition using mixture tying and consistency modeling

“…• Identifying the most likely subset of mixture components of the boot system for each cluster of HMM states Si and using these subsets Q (Si) c Q (S) as seed codebooks for the next phase • Copying the original eodebook multiple times (one for each cluster of states) and performing one iteration of the BaumWelch algorithm over the training data with the new tying scheme; the number of component densities in each codebook can then be reduced using clustering [10] 2,3, Reestimation…”