Speech Synthesis with Neural Networks
<|reference_start|>Speech Synthesis with Neural Networks: Text-to-speech conversion has traditionally been performed either by concatenating short samples of speech or by using rule-based systems to convert a phonetic representation of speech into an acoustic representation, which is then converted into speech. This paper describes a system that uses a time-delay neural network (TDNN) to perform this phonetic-to-acoustic mapping, with another neural network to control the timing of the generated speech. The neural network system requires less memory than a concatenation system, and performed well in tests comparing it to commercial systems using other technologies.<|reference_end|>
@article{karaali1998speech,
    title={Speech Synthesis with Neural Networks},
    author={Orhan Karaali, Gerald Corrigan and Ira Gerson},
    journal={World Congress on Neural Networks (1996) 45-50. San Diego},
    year={1998},
    archivePrefix={arXiv},
    eprint={cs/9811031},
    primaryClass={cs.NE cs.HC}
}