Although maximum mutual information (MMI) training has been used for hidden Markov model (HMM) parameter estimation for more than twenty years ([2], [8], [5], [9], and [14]), it has recently become an essential part of the acoustic modeling repertoire thanks to the refinements introduce
This paper reports our experiences with a phoneme recognition system for the TIMIT database which us...
The parameters of the standard Hidden Markov Model frame-work for speech recognition are typically t...
Discriminative training has become an important means for estimating model parameters in many statis...
Hidden Markov Models (HMMs) are one of the most powerful speech recognition tools available today. E...
Abstract – The paper presents theoretical and experimental issues related with Maximum Mutual Inform...
In this paper, we discuss some of the properties of training acoustic models using a lattice-free ve...
This paper describes a lattice-based framework for maximum mutual information estimation (MMIE) of H...
Discriminative training schemes, such as Maximum Mutual Information Estimation (MMIE), have been us...
A new training algorithm called the Approximated Maximum Mutual Information (AMMI) is proposed to im...
A new training algorithm called the approximated maximum mutual information (AMMI) is proposed to im...
This paper describes a framework for optimising the structure and parameters of a continuous density...
In this paper, we present an Equivalent-Class Based Maximum Mutual Information (ECB-MMI) learning me...
Discriminative training techniques for Hidden-Markov Models were recently proposed and successfully ...
[[abstract]]An algorithm for estimating the parameters of a hidden Markov model (HMM) is presented. ...
It is shown here that several techniques for masimum likelihood training of Hidden Markov Models are...
This paper reports our experiences with a phoneme recognition system for the TIMIT database which us...
The parameters of the standard Hidden Markov Model frame-work for speech recognition are typically t...
Discriminative training has become an important means for estimating model parameters in many statis...
Hidden Markov Models (HMMs) are one of the most powerful speech recognition tools available today. E...
Abstract – The paper presents theoretical and experimental issues related with Maximum Mutual Inform...
In this paper, we discuss some of the properties of training acoustic models using a lattice-free ve...
This paper describes a lattice-based framework for maximum mutual information estimation (MMIE) of H...
Discriminative training schemes, such as Maximum Mutual Information Estimation (MMIE), have been us...
A new training algorithm called the Approximated Maximum Mutual Information (AMMI) is proposed to im...
A new training algorithm called the approximated maximum mutual information (AMMI) is proposed to im...
This paper describes a framework for optimising the structure and parameters of a continuous density...
In this paper, we present an Equivalent-Class Based Maximum Mutual Information (ECB-MMI) learning me...
Discriminative training techniques for Hidden-Markov Models were recently proposed and successfully ...
[[abstract]]An algorithm for estimating the parameters of a hidden Markov model (HMM) is presented. ...
It is shown here that several techniques for masimum likelihood training of Hidden Markov Models are...
This paper reports our experiences with a phoneme recognition system for the TIMIT database which us...
The parameters of the standard Hidden Markov Model frame-work for speech recognition are typically t...
Discriminative training has become an important means for estimating model parameters in many statis...