  This paper describes the design of a neural network that performs the
phonetic-to-acoustic mapping in a speech synthesis system. The use of a
time-domain neural network architecture limits discontinuities that occur at
phone boundaries. Recurrent data input also helps smooth the output parameter
tracks. Independent testing has demonstrated that the voice quality produced by
this system compares favorably with speech from existing commercial
text-to-speech systems.
