musicperception and cognition - danish sound · 2019. 11. 1. · sofia dahl sof@create.aau.dk...

MUSIC PERCEPTION AND COGNITION

https://nordicsmc.create.aau.dk/

SOFIA DAHLDEPT. OF ARCHITECTURE, DESIGN AND MEDIA

TECHNOLOGY

Music as an embodied experience

”The embodied viewpoint holds that bodily involvement shapes the way weperceive, feel, experience, and comprehend music.”

• Movements encoded as musical sounds• The audio (and visual) modalities communicate expression• The first-person subjective experiences attribute intentions

Sofia Dahl sof@create.aau.dk

(Leman 2008, Godøy 2003)

(Leman, Nijs, Maes, Van Dyck 2017)

NON-VERBAL COMMUNICATION

Sofia Dahl sof@create.aau.dk

What about these faces? Which would you say is the friendlier looking?

Sofia Dahl sof@create.aau.dk

Demo

Turn to look at the person next at you ….while you sing and hold a note.

Sofia Dahl sof@create.aau.dk

Mock example of a picture pair similar to those used

high note

low note

What a lot of our participants did

(Huron, Dahl, Johnson, 2009; Ahrendt, Bach, Dahl 2017)Sofia Dahl sof@create.aau.dk

Musicians frequently display a varietymovements other than those actuallyproducing the sounds.

Sofia Dahl sof@create.aau.dk

• Four musical excerpts• Performed with intentions:

– HAPPINESS– SADNESS– ANGER– FEAR

• Two performers:– Soprano saxophone– Bassoon

Communicating expressive intent, Woodwind stimuli

(Dahl & Friberg, 2007)Sofia Dahl sof@create.aau.dk

Rating expressive intent and movements

Observers rated:• Emotional content

• Anger• Sadness• Happiness• Fear

• Movement cues• Amount

none - large • Speed

slow - fast• Fluency

jerky - smooth• Regularity

irregular- regular

(Dahl & Friberg 2004, 2007)Sofia Dahl sof@create.aau.dk

Combined results

(Dahl & Friberg, 2007)Sofia Dahl sof@create.aau.dk

0 1 2 3 4 5 6

0 1 2 3 4 5 6

large

fast

smooth

regularirregular

jerky

slow

none

large

fast

smooth

regular

large

fast

smooth

regular irregular

jerky

slow

none

irregular

jerky

slow

noneamount

speed

fluency

regularity

HAPPY INTENTION

mean rating

saxophone bassoon

large

fast

smooth

regular irregular

jerky

slow

none

0 1 2 3 4 5 6

amount

speed

fluency

regularity saxophonebassoon

ANGRY INTENTION

mean rating

0 1 2 3 4 5 6

amount

speed

fluency

regularity

FEARFUL INTENTION

mean rating

saxophone bassoon

amount

speed

fluency

regularity

saxophone bassoon

mean rating

SAD INTENTION

Movement ratings of woodwind performances

(Dahl & Friberg, 2007)Sofia Dahl sof@create.aau.dk

Perceptually relevant cues for movement and audio

amount speed fluency regularity

Happiness large fast

Sadness small slow smooth regular

Anger large fast jerky irregular

Fear small jerky irregular

amountsound level

speedTempo

fluencyarticulation

regularitytempo var.

Happiness large

highfast

fast staccato smallSadness small

lowslow

slowsmooth

legatoregular

final ritardAnger large

highfast

fastjerky

staccatoirregular

smallFear small

low fastjerky

staccatoirregular

large

(Dahl & Friberg, 2007; Juslin, Friberg & Bresin,2002)Sofia Dahl sof@create.aau.dk

RHYTHMIC MOVEMENTS AND ENTRAINMENT

Sofia Dahl sof@create.aau.dk

Synchronization and entrainment to a beat or pulse• Not unique to our species

• …but we find it highly pleasurable

Coordinating Drumming Movements

Time (s)0 0.5 1 1.5 2 2.5 3

Vert

ical d

ispla

cem

ent (m

m)

100

200

300

400

500

600

700

800

900

1000

1100

(Godøy, Song & Dahl, 2017; Dahl, 2018)

Collaboration within NordicSMC

https://www.uio.no/ritmo/english/projects/flagship-projects/

Playing with different timing instructions

Velocity profile of left drumstick for a player playing ahead, on or behindmetronome

Sofia Dahl sof@create.aau.dk

”Pushed” ”On” ”Laid Back”

Bodily responses to (rhythmic) music

• Music can be a fantastic motivator for engaging in body movement!

Sofia Dahl sof@create.aau.dk

Dancing: A whole body activity in synchrony with music

Sofia Dahl sof@create.aau.dk

What determines what we find comfortable to move to?

Musical tempi covers a wide range, but not all suitable for dancing

If we “bounce” to the rhythm, our body shape (morphology) could have an influence

30 participants’Preferred beat period (ms)vs.Average leg length

75 80 85 90 95 100

200

300

400

500

600

700

Average leg length (cm)

Pre

ferr

ed b

eat r

ate

(ms)

(Dahl, Huron, Brod, Altenmüller 2014)Sofia Dahl sof@create.aau.dk

“Try out different tempi and select your preferred”

Rhythmic Recurrency in Dance to Music with Ambiguous Meter

How do groups ofparticipants move to music where the metric structure is ambiguous?

Sofia Dahl sof@create.aau.dk (Dahl & Sioros,2018)

A B C D

0 20 40 60 80 100 120 140 160 180

0

0.1

0.2

0

0.1

0.2

12345

participant

1234

participantReccurence�Rate

group�1group�2

Time�(sec)

melody melody melodyhighly synchopated

(Dahl & Sioros,2018)Sofia Dahl sof@create.aau.dk

https://nordicsmc.create.aau.dk/

THANK YOU!

References• Ahrendt, P., Bach, C. C., & Dahl, S. (2017). Does Singing a Low-Pitch Tone Make You Look Angrier? Proceedings of the

14th Sound and Music Computing Conference 2017, 181–187. Aalto University.• Dahl, S., & Friberg, A. (2004). Expressiveness of musician’s body movements in performances on marimba. In A. Camurri &

G. Volpe (Eds.), Gesture-based Communication in Human-Computer Interaction; Lecture Notes in Artificial Intelligence (Vol. 2915, pp. 479–486). Berlin, Heidelberg: Springer Verlag.

• Dahl, S., & Friberg, A. (2007). Visual perception of expressiveness in musicians’ body movements. Music Perception: An Interdisciplinary Journal, 24(5), 433–454.

• Dahl, S., Brod, G., & Altenmüller, E. (2014). Preferred Dance Tempo: Does Sex or Body Morphology influence how wegroove? Journal of New Music Research, 43(2), 214–223.

• Dahl, S., & Sioros, G. (2018). Rhythmic Recurrency in Dance to Music with Ambiguous Meter. Proceedings of the 5th International Conference on Movement and Computing, 38:1–38:6. https://doi.org/10.1145/3212721.3212885

• Dahl, S. (2018). Movements, timing and precision of drummers. In B. Müller, S. Wolf, G.-P. Brueggemann, Z. Deng, A. McIntosh, F. Miller, & W. Scott Selbie (Eds.), Handbook of Human Motion. Springer.

• Godøy, R. I. (2003). Motor-mimetic music cognition. Leonardo, 36(4), 317–319.• Godøy, R. I., Song, M., & Dahl, S. (2017). Exploring sound-motion textures in drum set performance. Proceedings of the

Sound and Music Computing Conference, 145–152.• Huron, D., Dahl, S., & Johnson, R. (2009). Facial Expression and Vocal Pitch Height: Evidence of an Intermodal Association.

Empirical Musicology Review, 4(3), 93–100.• Juslin, P. N., Friberg, A., & Bresin, R. (2002). Toward a computational model of expression in performance: The GERM

model. Musicae Scientiae, (Special issue 2001-2002), 63–122.• Leman, M. (2008). Embodied music cognition and mediation technology. Mit Press.• Leman, M., Maes, P.-J., Nijs, L., & Van Dyck, E. (2018). What is embodied music cognition? In Springer handbook of

systematic musicology (pp. 747–760). Springer.