Chord Generation from Symbolic Melody Using BLSTM Networks

Understand

Generating a chord progression from a monophonic melody is a challenging problem because a chord progression requires a series of layered notes played simultaneously.

• This paper presents a novel method of generating chord sequences from a symbolic melody using bidirectional long short-term memory (BLSTM) networks trained on a lead sheet database.
• To this end, a group of feature vectors composed of 12 semitones is extracted from the notes in each bar of monophonic melodies.
• In order to ensure that the data shares uniform key and duration characteristics, the key and the time signatures of the vectors are normalized.