A High Quality Text-To-Speech System Composed of Multiple Neural Networks
<|reference_start|>A High Quality Text-To-Speech System Composed of Multiple Neural Networks: While neural networks have been employed to handle several different text-to-speech tasks, ours is the first system to use neural networks throughout, for both linguistic and acoustic processing. We divide the text-to-speech task into three subtasks, a linguistic module mapping from text to a linguistic representation, an acoustic module mapping from the linguistic representation to speech, and a video module mapping from the linguistic representation to animated images. The linguistic module employs a letter-to-sound neural network and a postlexical neural network. The acoustic module employs a duration neural network and a phonetic neural network. The visual neural network is employed in parallel to the acoustic module to drive a talking head. The use of neural networks that can be retrained on the characteristics of different voices and languages affords our system a degree of adaptability and naturalness heretofore unavailable.<|reference_end|>
@article{karaali1998a,
    title={A High Quality Text-To-Speech System Composed of Multiple Neural
  Networks},
    author={Orhan Karaali, Gerald Corrigan, Noel Massey, Corey Miller, Otto
  Schnurr and Andrew Mackie},
    journal={Proceedings of the IEEE International Conference on Acoustics,
  Speech and Signal Processing (1998) 2:1237-1240. Seattle, Washington},
    year={1998},
    doi={10.1109/ICASSP.1998.675495},
    archivePrefix={arXiv},
    eprint={cs/9812006},
    primaryClass={cs.NE cs.HC}
}