论文标题
怪异的ai yankovic：产生模仿歌词
Weird AI Yankovic: Generating Parody Lyrics
论文作者
论文摘要
歌词模仿互换了一组旋律，上面有一组新的单词，可以保留每行音节的数量和押韵方案。歌词模仿生成是可控文本生成的挑战。我们展示了专业的抽样程序如何与XLNET的落后文本生成相结合可以可靠地符合音节和韵律方案约束。我们以神经抒情模仿产生的社会意义得出结论。
Lyrics parody swaps one set of words that accompany a melody with a new set of words, preserving the number of syllables per line and the rhyme scheme. Lyrics parody generation is a challenge for controllable text generation. We show how a specialized sampling procedure, combined with backward text generation with XLNet can produce parody lyrics that reliably meet the syllable and rhyme scheme constraints.We introduce the Weird AI Yankovic system and provide a case study evaluation. We conclude with societal implications of neural lyric parody generation.
