  We present EMPHASIS, an emotional phoneme-based acoustic model for speech
synthesis system. EMPHASIS includes a phoneme duration prediction model and an
acoustic parameter prediction model. It uses a CBHG-based regression network to
model the dependencies between linguistic features and acoustic features. We
modify the input and output layer structures of the network to improve the
performance. For the linguistic features, we apply a feature grouping strategy
to enhance emotional and prosodic features. The acoustic parameters are
designed to be suitable for the regression task and waveform reconstruction.
EMPHASIS can synthesize speech in real-time and generate expressive
interrogative and exclamatory speech with high audio quality. EMPHASIS is
designed to be a multi-lingual model and can synthesize Mandarin-English speech
for now. In the experiment of emotional speech synthesis, it achieves better
subjective results than other real-time speech synthesis systems.
