Interval type-2 fuzzy hidden Markov models
Jia Zeng, Zhi-Qiang Liu · 2005
This paper presents an extension of the hidden Markov models (HMMs) using interval type-2 fuzzy sets (FSs) and fuzzy logic systems (FLSs) to produce interval type-2 FHMMs. The advantage of this extension is that it can handle both the randomness and fuzziness. Membership function (MF) of the type-2 FS is three-dimensional. It is the third-dimension that provides additional degrees of freedom to evaluate HMM's uncertainties. An attractive property of this extension is that if all uncertainties disappear, the interval type-2 FHMM reduces to the classical HMM. We apply our interval type-2 FHMM as an acoustic model for phoneme recognition on TIMIT speech database. Experimental results show that the type-2 FHMM has a comparable performance as that of the HMM but is more robust to the speech variation, while it retains almost the same computational complexity as that of the HMM.