Automatic generation of multiple pronunciations based on neural networks

We propose a method for automatically generating a pronunciation dictionary based on a pronunciation neural network that can predict plausible pronunciations (realized pronunciations) from the canonical pronunciation. This method can generate multiple forms of realized pronunciations using the pronunciation network. For generating a sophisticated realized pronunciation dictionary, two techniques are described: (1) realized pronunciations with likelihoods and (2) realized pronunciations for word boundary phonemes. Experimental results on spontaneous speech show that the automatically derived pronunciation dictionaries give consistently higher recognition rates than a conventional dictionary.