We would like to use features that look at wide context on the input side , which is inexpensive ( Jiampojamarn et al. , 2007 ) .
applying manytomany alignments and hidden markov models to lettertophoneme conversion
Sittichai Jiampojamarn Grzegorz Kondrak Tarek Sherif
In future work , we would like to identify a set of features , latent variables , and training methods that port well across languages and string-transduction tasks . We would like to use features that look at wide context on the input side , which is inexpensive ( Jiampojamarn et al. , 2007 ) . Latent variables we wish to consider are an increased number of word classes ; more flexible regions -- see Petrov et al. ( 2007 ) on learning a state transition diagram for acoustic regions in phone recognition -- and phonological features and syllable boundaries .
We would like to use features that look at wide context on the input side , which is inexpensive ( @@CITATION ) .