| dc.description.abstract | This paper focuses on the technology of high quality dictation system based on neural network and extends the related design and application. The biggest difference is that we have more training materials, faster hardware and more Variety can be used in the voice synthesis of other enhanced technology, so that the quality of synthetic speech more close to the real voice. To make this technology can be applied to life, the need to design flexible and support multi-technology tools for implementation, the system is mainly developed in Python language, installed on the Linux operating system, you need a support for external front-end features Tools, the front-end output format must be state-level alignment of the HTS tag, currently supports two voice coder (vocoder): STRAIGHT and WORLD, before training the neural network, the language features using min-max regular And the output acoustic feature is normalized with mean-variance. As for the principle of Acoustic Modeling, the Feedforward Neural Network and Long Short-Term Memory based (RNN) are implemented in the system. In addition, the characteristics and strengths of the system, respectively, introduced three related applications. Finally, it is also looking forward to this system, in addition to constantly in the quality and efficiency on the sophisticated, but also to promote the various needs of Taiwan. | en_US |