Pinyin Conversion Based On Neural Networks

The conversion of PINYIN to Chinese characters is an important content of the NLP (Natural Language Processing). This paper bases on the research of Braille-Chinese conversion. The Braille can easily transform to PINYIN, so the translation of Braille and Chinese is actually PINYIN-Chinese conversion. Basically there are two NLP methods - Rule Based Method and Statistic Based Method. And the system of this paper belongs to the Statistic Based Method. It is more easily to implement. We first discuss the theory of PINYIN ?Chinese Conversion and then review some methods in use, Especially the method based on Hidden Markov Model. We discuss the disadvantage of the method then introduce a PINYIN-Chinese conversion method based on Artificial Neural Network (ANN). We give the structure of the system, and we design and implement two systems. One uses BP network and another uses Recurrent Neural Network (RNN). And then we discuss BP (back propagation) algorithm and BPTT (back propagation through time) algorithm, which is used to train the two networks. We also show an algorithm called output-increase to perform the training. And we give an ANN-viterbi mixed algorithm to do the conversion. The function of each module is showed. And then keystone of the system is discussed. At last we analyze the result of the experiment and discuss the way of improvement.