Loading...
We present a theoretical investigation into the use of normalised artificial neural network (ANN) outputs in the context of hidden Markov models (HMMs). The work is motivated by the pursuit of a more theoretically rigorous understanding of the Kullback-Liebler (KL)-HMM. Two possible models are considered based respectively on the HMM states storing categorical distributions and Dirichlet distributions. Training and recognition algorithms are derived, and possible relationships with KL-HMM are briefly discussed.
Loading...
Name
Garner_Idiap-RR-11-2013.pdf
Access type
openaccess
Size
480.53 KB
Format
Adobe PDF
Checksum (MD5)
02f8e69fb5500d024f622c667299442d