Guangcan Liu
2022
ChipSong: A Controllable Lyric Generation System for Chinese Popular Song
Nayu Liu
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Wenjing Han
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Guangcan Liu
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Da Peng
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Ran Zhang
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Xiaorui Wang
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Huabin Ruan
Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)
In this work, we take a further step towards satisfying practical demands in Chinese lyric generation from musical short-video creators, in respect of the challenges on songs’ format constraints, creating specific lyrics from open-ended inspiration inputs, and language rhyme grace. One representative detail in these demands is to control lyric format at word level, that is, for Chinese songs, creators even expect fix-length words on certain positions in a lyric to match a special melody, while previous methods lack such ability. Although recent lyric generation community has made gratifying progress, most methods are not comprehensive enough to simultaneously meet these demands. As a result, we propose ChipSong, which is an assisted lyric generation system built based on a Transformer-based autoregressive language model architecture, and generates controlled lyric paragraphs fit for musical short-video display purpose, by designing 1) a novel Begin-Internal-End (BIE) word-granularity embedding sequence with its guided attention mechanism for word-level length format control, and an explicit symbol set for sentence-level length format control; 2) an open-ended trigger word mechanism to guide specific lyric contents generation; 3) a paradigm of reverse order training and shielding decoding for rhyme control. Extensive experiments show that our ChipSong generates fluent lyrics, with assuring the high consistency to pre-determined control conditions.
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Co-authors
- Nayu Liu 1
- Wenjing Han 1
- Da Peng 1
- Ran Zhang 1
- Xiaorui Wang 1
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