5. 1. ベーシストの旋律分析
A Pattern Recognition Approach to Analyze
Temporal Evolution of a Bassist's Musical Styles
Y. Matsuura, T. Tanahashi, and T. Kitahara
Proc. CSMC 2017
6. Background
●
Bass is an important part from both rhythmic &
harmonic aspects of music
●
Bassists have their own styles in bass phrases
●
But their styles evolve due to:
– changes in their musical preferences,
– changes in musical trends,
– changes in band members,
– etc.
Year 1989
Year 1989
『
『Higher Ground
Higher Ground』
』
Year 1999
Year 1999
『
『Parallel Universe
Parallel Universe』
』
Red Hot Chili Peppers
Ba.
Ba. Ba.
Ba.
■
7. Background
●
Such evolution is qualitatively mentioned in
commercial music magazines
●
But few attempts to investigate them quantitively
“By realizing John Frusciante’s swelled ideas,
the band has shifted its musical style to
being focused on the vocal.”
“Flea began to play bass lines that support
the vocals with his vintage jazz bass.”
(originally in Japanese; translated by us)
8. Our aim
●
Extract features from MIDI
data of his 1st
- and 2nd
-half
bass melodies
●
Classify them with pattern
recognition methods
●
Investigate features that
contributes to accurate
classification
To investigate the temporal evolution of a bassist’s
musical styles in a quantitative approach
Target bassist
Flea (Red Hot Chilli Peppers)
Our approach
9. What’s commonly known about Flea
1999
John Frusciante
(guitarist) came back
Active bass lines
- Low pitch range
- Pitch moves up and down
- Often use slapping
Simple bass lines
- High pitch range
- Pitch doesn’t move largely
- Enhance vocals
Year 1989
Year 1989
『
『Higher Ground
Higher Ground』
』
Year 1999
Year 1999
『
『Parallel Universe
Parallel Universe』
』
Ba.
Ba.
Ba.
Ba.
10. Data
Year Album name #pieces
1989 Mother's Milk 13
1991 Blood Sugar Sex Magik 17
1999 Californication 15
2002 By the Way 16
2006 Stadium Acadium 28
2011 I'm with You 14
●
We made MIDI data from scores
●
Timbral or expressive features are not available
11. Feature extraction
●
Pitch-based features (P-1 to P-37)
– P-1: Mean pitch through the whole piece
– P-2: Num of note seqs having the same note number
– ...
●
Duration-based features (D-1 to D-9)
– D-1: Mean duration in all notes
– D-3: Ratio of num of successive note pairs with different
durations
– ...
●
Count-based features (C-1 to C-11)
– C-1: Num of notes in the whole piece
– ...
(1 vector from
a whole piece)
12. Experiment 1: Division of period
●
Classify of 1st
- and 2nd
-period bass melodies
●
Flea’s style is considered to have changed in 1999
●
Classification should be the most accurate when
the boundary is set to 1999
Year Album name #pieces
1989 Mother's Milk 1st
period
３０
1991 Blood Sugar Sex Magik
1999 Californication
2nd
period
７３
2002 By the Way
2006 Stadium Acadium
2011 I'm with You
13. Results
J48 IBk BayesNet
Multilayer
Perceptron
1999
1999 76%
76% 78%
78% 73%
73% 84%
84%
2002 61% 54% 61% 63%
2006 65% 55% 62% 50%
The boundary of 1999 made the highest accuracy
Bass styles actually changed in 1999
(10-fold cross validation)
14. Experiment 2: Feature selection
●
Search a small feature set maximizing accuracy
●
Selected features illustrate changes in bass lines
●
Analyze important features with decision trees
15. Selected features
●
P-1: Mean pitch
●
P-6: Num of successive note pairs where
the absolute diff. in the note nums is 3
●
P-16: Ratio of successive note pairs where
the absolute diff. in the note nums is 0
●
C-10: Ratio of notes with top 5 note nums
Pitch
Local
pitch
motions
Pitch
variation
Only with 4 features,
we obtain 82% accuracy
16. Obtained decision tree
P-1: Mean pitch P-6: Num of
succ note pairs
where abs diff in
note nums is 3
C-10: Ratio of notes
with top 5 note nums
P-1: Mean pitch
17. Discussion Magazines and web sites say:
●
Since the album “Californication”, Anthony Kiedis’s vocal
has been melodious, and accordingly Flea’s bass line has
become snuggled up to the melodies
●
“By The Way” has been surprisingly a John-centric work.
Following the melody-enhanced line shown in the previous
work, in “Don’t Forget Me” for example, the guitar sounding
tremolos madly plays the leading role; Flea dryly plays the
chord progression behind it.
●
In “Californization”, released after John Frusciante came back,
melodious songs increased. The sound on the basis of
Anthony’s “singing” vocal confirm that this band has
proceeded to a new step.
●
By realizing John Frusciante’s swelled ideas, the band has
shifted its musical style to being focused on the vocal. At the
same time, Flea began to play bass lines that support the
vocals with his vintage jazz bass.
18. Discussion
1999
John Frusciante
(guitarist) came back
Active bass lines
- Low pitch range
- Pitch moves up and down
- Often use slapping
Simple bass lines
- High pitch range
- Pitch doesn’t move largely
- Enhance vocals
Selected features
●
Overall mean pitch
●
Local pitch motions
●
Pitch variation
To summarize
Selected features match
well-known tendencies
19. 2. イコライザーの印象分析
An Investigation towards Verbally Controllable
Graphic Equalizer for Singing Voices
S. Masuda, E. Aiba, and T. Kitahara
Proc. WIMP 2019
21. Motivation
●
Recently, many amateur singers publish their
singing performances on YouTube etc.
Why Because the cost is decreasing
(PC, audio I/F, and DAW software)
Problem Processing voices is not easy
Record voice Equalize (EQ)
Use other
effects
Mix with
backing track
12dB cut at
125-1000 Hz
12dB boost
at 2-16 kHz
- EQ is important to obtain
their desired timbre
- but not easy for people
without know-how
22. Goal
●
To enable amateur singers to equalize their voices
in an intuitive way
Key idea We often verbally express sounds
(e.g. bright sounds, warm sounds)
Control EQ with verbal expression
Verbally Controllable Equalizer
Bright-
ness
Warm-
ness
......
500 Hz 2 kHz 8 kHz
Specified
by the user
Automatically
obtained
23. Sound stimuli (recording)
●
Song: "Yoake to Hotaru" (Nabuna)
●
Sung by the 1st
author
●
Recorded only singing voice
●
Mic: ATAT4040 (Audio Technica)
●
Audio I/F: UM2 (Behringer)
>
Participants
●
11 university students
– 4 have experience in musical performances
– 1 has experience in DAW
Investigation of relationship between EQ
settings and verbal evaluation
24. Sound stimuli (EQ)
●
Used Cubase 7.5
●
Treated the 10-band EQ
as a 4-band EQ
– Lowest F0: 112 Hz
●
Prepared 27 stimuli
– not EQ
– 1 band boosted by 12 dB
– 1 band cut by 12 dB
– 2 bands boosted by 12dB
– 1 band boosted by 12 dB and 1 band cut by 12 dB
●
RMS is normalized
excluded
125-250Hz
500-1000Hz 8-16kHz
2-4kHz
26. Selection of Sound Expression Words
●
Extracted 10 words expressing the effects of EQ
from EQ know-how books for hobby musicians
●
Words: 暖かさ (warmness), 存在感 (presence), 派手さ
(showiness), 濁り (muddiness), まろやかさ (mellowness),
柔らかさ (softness), 明るさ (brightness), 軽さ (lightness),
太さ (thickness), クリアさ (clearness)
27. Procedure
1. Listen to both pre-EQ & EQed stimuli
2. Evaluate how stronger the characteristics
expressed by each word became through EQ
Example of evaluations
Warmness >
Showiness >
Clearness >
Timeline
4.3 cm
Pre-EQ
1.3 cm
Rest
(3s)
13.9 cm
EQed stimulus
(evaluate it during this)
1.3 cm
Rest
(10s)
28. Result of linear regression
● Approximated the average yj
of the participants’
evaluations w.r.t. word j as yj
~ bj0
+ Σ bjk
xk
(where xk
is boost/cut level at each freq. range)
The results match descriptions in know-how books
29. Application to verbal EQ controller
We implemented a prototype on GNU Octave
Verbal controller
Direct controller
Mutually transformable
