Challenge: Existing systems based on attributes or keywords render lyrics generation very limited . previous studies focused on generating lyrics based only on attributes and keywords .
Approach: They propose to use Chinese passage-level text as input for lyrics generation . they initialize parameters with custom pretrained Chinese GPT-2 model and adopt a two-step process to fine-tune the model for better alignment between passage- level text and lyrics.
Outcome: The proposed system is conditioned on passage-level text rather than attributes or keywords, rendering limited control over the content of the lyrics.

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Challenge: Existing methods of generating singable lyrics are based on a given melody, but there are two main challenges: generating the lyrics without knowing the melody and composing compatible melodies.
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Challenge: Existing models for lyrics generation are insufficient to capture relationship between lyrics and melody.
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Challenge: Existing methods for automatic melody-to-lyric generation are limited due to the limited amount of melody-lyrical aligned data.
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Challenge: Existing studies on lyrics generation focus on generating accurate lyrics using keywords, rhymes, etc. However, there is no parallel corpus for lyrics imitation.
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Challenge: Creating lyrics and melodies in symbolic format requires expert knowledge of melody and an advanced understanding of lyrics.
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Challenge: a new method for generating lyrics for Mandarin songs is based on scansion . the number of syllables required is variable due to the number and number of notes .
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Challenge: Existing works ignore musical attributes hidden behind lyrics and structure of lyrics . existing works ignore structure of generated lyrics and do not consider structure of songs .
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