Add to ORKGProceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 20102982-298
The conditional independence assumption imposed by the hidden Markov models (HMMs) makes it difficul...
Speech recognition systems that are based on hidden Markov modeling (HMM), assume that the mean traj...
This thesis describes work developing an approach to automatic speech recognition which incorporates...
10.1109/ICASSP.2012.6288983ICASSP, IEEE International Conference on Acoustics, Speech and Signal Pro...
Parametric trajectory models explicitly represent the tem-poral evolution of the speech features as ...
Recently, implicit trajectory modelling using temporally varying model parameters has achieved promi...
ASA-EAA2008: the 2nd Joint meeting of the Acoustical Society of America at the European Acoustical A...
This paper shows that the HMM whose state output vector includes static and dynamic feature paramete...
This paper shows that the HMM whose state output vector includes static and dynamic feature paramete...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1994....
Contains fulltext : 42030.pdf (publisher's version ) (Closed access)4 september 20...
Abstract We have shown that the HMM whose state output vector includes static and dynamic feature pa...
International audienceIn this paper, a unified trajectory model based on the stylization and the mod...
In this paper we report on attempting to capture segmen-tal transition information for speech recogn...
It is well known that frame independence assumption is a fundamental limitation of current HMM based...
The conditional independence assumption imposed by the hidden Markov models (HMMs) makes it difficul...
Speech recognition systems that are based on hidden Markov modeling (HMM), assume that the mean traj...
This thesis describes work developing an approach to automatic speech recognition which incorporates...
10.1109/ICASSP.2012.6288983ICASSP, IEEE International Conference on Acoustics, Speech and Signal Pro...
Parametric trajectory models explicitly represent the tem-poral evolution of the speech features as ...
Recently, implicit trajectory modelling using temporally varying model parameters has achieved promi...
ASA-EAA2008: the 2nd Joint meeting of the Acoustical Society of America at the European Acoustical A...
This paper shows that the HMM whose state output vector includes static and dynamic feature paramete...
This paper shows that the HMM whose state output vector includes static and dynamic feature paramete...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1994....
Contains fulltext : 42030.pdf (publisher's version ) (Closed access)4 september 20...
Abstract We have shown that the HMM whose state output vector includes static and dynamic feature pa...
International audienceIn this paper, a unified trajectory model based on the stylization and the mod...
In this paper we report on attempting to capture segmen-tal transition information for speech recogn...
It is well known that frame independence assumption is a fundamental limitation of current HMM based...
The conditional independence assumption imposed by the hidden Markov models (HMMs) makes it difficul...
Speech recognition systems that are based on hidden Markov modeling (HMM), assume that the mean traj...
This thesis describes work developing an approach to automatic speech recognition which incorporates...