Automatic Generation of Children's Songs Based on Machine Statistic Learning

Abstract

In this paper, the automatic generation of children's songs is studied. First of all, according to the number of key lyrics submitted by the songwriter, statistical machine learning is used to expand and obtain more theme-related lyrics, and then the first sentence is generated through the language model automatically. On this basis, the subsequent sentences are generated through the statistical machine learning translation method. In the process of the generation, the statistical machine learning is used to expand the conception of the song, so as to get richer sentence candidates. The main features and contributions of the study are: Firstly, the statistical machine learning translation is put forward as the theoretical basis, the preceding and next sentence relationship of children's songs are mapped into the relation of the source language and target language in the statistical translation model, and the machine statistics learning translation model is designed with the integration of the domain knowledge of songs. Secondly, the statistical machine learning is used in the generation process to expand the lyrics words, thereby enhancing the theme and conception of the song. The experimental results have confirmed the effectiveness of the proposed method.