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Humming Transcription
• Humming transcription
– Our front-end for music search
– Goal: Convert humming into an MIDI note
sequence
• Steps involved in humming transcription
1. Track pitch over the humming input
2. Identify notes via silence
3. Find the best MIDI sequence (of integer
semitones) via key transposition
Pitch Tracking over the Humming
4
• Pitch tracking methods
• Example:
– Humming input
– Identified pitch vector
– Notes are identified by
volume or clarity
thresholding
2
0
-2
1
2
3
4
5
6
7
8
9
10
6
7
8
9
10
6
7
8
9
10
5
6
Time (sec)
7
8
9
10
Computed pitch
Pitch (semitone)
– ACF-based peak picking
– ACF-based dynamic
programming
Waveform of roger.wav
x 10
60
55
50
1
2
3
4
6
4
5
Volume
x 10
2
0
1
2
3
4
5
Clarity
1
0.5
0
1
2
3
4
MIDI Sequence Identification
0.5
• We need to represent each
note as an integer semitone
(or the so-called MIDI number)
Mean deviation (semitone)
0.45
– Perform exhaustive search on
pitch shift to identify the best
integer semitones
0.25
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
Shift (semitone)
60
0.2
0.3
0.4
0.5
Best shifted pitch vector
Best identified MIDI numbers
58
Pitch (Semitone)
2.
Notes obtained as medians
from pitch vector: [50.56,
49.45, 56.46, 56.36, 58.82,
58.65, 56.70, 54.74, 54.93,
53.85, 53.70, 51.53, 51.73,
49.62]
Best integer notes after key
transposition: [50, 50, 57, 57,
59, 59, 57, 55, 55, 54, 54, 52,
52, 50]
0.35
0.3
• Example
1.
0.4
56
54
52
50
1
2
3
4
5
6
Time (sec)
7
8
9
10
Humming Transcription
• Humming transcription is our front-end for music
search.
• The process for humming transcription
1. Typical humming
2. Pitch vector obtained from ACF: [0, 0, 49.5336, 49.4312,
49.4817, 50.0910, 0, 50.5623, ...]
3. Median notes obtained from pitch vector: [50.5623,
49.4559, 56.4628, 56.3636, 58.8217, 58.6510, 56.7025,
54.7415, 54.9399, 53.8507, 53.7002, 51.5369, 51.7357,
49.6283]
4. Best integer notes after key transposition: [50, 50, 57, 57,
59, 59, 57, 55, 55, 54, 54, 52, 52, 50]