Automatic generation of phone sets and lexical transcriptions

Large vocabulary automatic speech recognition systems model words as sequences of a small set of basic sub-word units (the phoneset), which the systems are trained to classify. All words in the system´s vocabulary are transcribed in terms of this set in a dictionary. The phoneset and dictionary are specific to a language and are typically designed manually. The system´s performance is critically dependent on the quality of the phoneset and the accuracy of the dictionary. The authors attempt to generate the phoneset and dictionary automatically, using only the training data and their transcriptions. We treat this as a joint optimization problem with a maximum a posteriori solution for the dictionary and a maximum likelihood solution for the phoneset and its acoustic models. Experiments with the DARPA Resource Management corpus show that the automatically generated phoneset and dictionary result in recognition accuracies close to those obtained using manually designed ones