HMM2- A Novel Approach to HMM Emission Probability Estimation
In this paper, we discuss and investigate a new method to estimate local emission probabilities in the framework of hidden Markov models (HMM). Each feature vector is considered to be a sequence and is supposed to be modeled by yet another HMM. Therefore, we call this approach `HMM2'. There is a variety of possible topologies of such HMM2 systems, e.g. incorporating trellis or ergodic HMM structures. Preliminary HMM2 speech recognition experiments on cepstral and spectral features yielded worse results than state-of-the-art systems. However, we believe that HMM2 systems have a lot of potential advantages and are therefore worth investigating further.
- URL: http://publications.idiap.ch/downloads/reports/2000/rr00-30.pdf
- Related documents: http://publications.idiap.ch/index.php/publications/showcite/weber-rr-00-30
Record created on 2006-03-10, modified on 2016-08-08