An interesting aspect of our generative approach is that we model HMM outputs as Gaussian vectors ( log probabilities of observing entire sentences based on our language models ) , as opposed to sequences of terms , as done in ( Barzilay and Lee , 2004 ) .
catching the drift probabilistic content models with applications to generation and summarization
Regina Barzilay Lillian Lee
An interesting aspect of our generative approach is that we model HMM outputs as Gaussian vectors ( log probabilities of observing entire sentences based on our language models ) , as opposed to sequences of terms , as done in ( Barzilay and Lee , 2004 ) . This technique provides two important advantages .
An interesting aspect of our generative approach is that we model HMM outputs as Gaussian vectors ( log probabilities of observing entire sentences based on our language models ) , as opposed to sequences of terms , as done in ( @@CITATION ) .