This paper describes an improved input coding method for a textto- phoneme (TTP) neural network model for speaker independent speech recognition systems. The code-book is self-organizing and is jointly optimized with the TTP model ensuring that the coding is optimal in terms of overall performance. The codebook is based on a set of single layer neural networks with shared weights. Experiments show that performance is increased compared to the NETTalk and NETSpeak models.
Cite as: Jensen, K.J., Riis, S. (2000) Self-organizing letter code-book for text-to-phoneme neural network model. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 3, 318-321, doi: 10.21437/ICSLP.2000-540
@inproceedings{jensen00b_icslp,
author={Kare Jean Jensen and Søren Riis},
title={{Self-organizing letter code-book for text-to-phoneme neural network model}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 3, 318-321},
doi={10.21437/ICSLP.2000-540}
}