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.


Published in:
International Conference on Spoken Langugae Processing (ICSLP 2000), III.147-150
Presented at:
International Conference on Spoken Langugae Processing (ICSLP 2000)
Year:
2000
Publisher:
Beijing, China
Keywords:
Note:
IDIAP-rr 00-30
Laboratories:




 Record created 2006-03-10, last modified 2018-01-27

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