BandNet: Neural Network-Based Multi-Instrument Music Composition

 
BandNet: A Neural Network-Based, Multi-Instrument
Beatles-Style MIDI Music Composition Machine
 
Yichao Zhou
1,2
    
Wei Chu
1
   Sam Young
1,3
    Xin Chen
1
 
1
Snap Inc.     
2
EECS,
 
University of California, Berkeley.
3
Herb
 
Alpert
 
School
 
of
 
Music,
 
University of California, Los Angeles
.
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Encoding the Score
 
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 E4
NEXT_CHANNEL
NEW_NOTE
 C3
 
NEXT_STEP
 
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NEW_NOTE
 G3
NEW_NOTE
 C3
 
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Melody
 
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Music Assemble Pipeline
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Results
 
(Subjective
 
Listening)
We asked subjects to listen to 
14
 testing
songs 
and
 
answer the questions
 
(1-5):
1.
Does it sound similar to the music
from
 the Beatles?
2.
How likely is it that this music was 
professionally composed?
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How interesting is this music?
  
Style
 
Similarity
      
Profession
         
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Thank you for listening!
 
Slide Note

Good afternoon, everyone, I am Yichao Zhou from UC Berkeley. I will present our work, BandNet: A Neural Network-Based, Multi-Instrument Beatles-Style MIDI Music Composition Machine.

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This research project introduces BandNet, a neural network-based system for multi-instrument Beatles-style MIDI music composition. By encoding musical scores using LSTM-RNN, the system addresses limitations of existing works and supports generating music scores for various purposes. Users can engage in the music assembly pipeline, selecting music clips and structuring songs based on a provided template. Results indicate subjective listening feedback on the music's similarity to The Beatles, perceived professionalism, and overall interest.

  • Music Composition
  • Neural Network
  • Multi-Instrument
  • Beatles
  • LSTM-RNN

Uploaded on Aug 11, 2024 | 0 Views


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  1. BandNet: A Neural Network-Based, Multi-Instrument Beatles-Style MIDI Music Composition Machine Yichao Zhou1,2 Wei Chu1Sam Young1,3 Xin Chen1 1Snap Inc. 2EECS, University of California, Berkeley. 3Herb Alpert School of Music, University of California, Los Angeles.

  2. Computer Music Composition GOAL: Automatically generate music scores Generate musics for photo albums Build royalty-free sound libraries Harmonize vocal singing

  3. The Beatles Dataset 123 MIDI files from The Beatles 4 labelled channels Melody (vocal part) Chords (harmony part) Bass Drum

  4. Challenges Limitation of existing works (Magenta, FolkRNN, BachBot) Cannot support multiple instruments (Band!) Lack of song structure

  5. Encoding the Score LSTM-RNN: How to deal with multiple instruments? RNN only takes a sequence as input NEW_NOTE E4 NEXT_CHANNEL NEW_NOTE C3 Melody NEXT_STEP CONTINUE_NOTE E4 NEXT_CHANNEL NEW_NOTE G3 NEW_NOTE C3 Bass NEXT_STEP

  6. Music Assemble Pipeline 1. Users pick a seed for the each section; 2. LSTM-RNN generates music clips for each section; 3. Users listen to the clips and choose the one they like; 4. BandNet assembles the whole song according to a music structure template

  7. Results (Subjective Listening) We asked subjects to listen to 14 testing songs and answer the questions (1-5): 1. Does it sound similar to the music from the Beatles? How likely is it that this music was professionally composed? How interesting is this music? 2. 3. Style Similarity Profession Interestingness

  8. Thank you for listening!

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