Music and the Cognitive Sciences 1990

Name: Music and the Cognitive Sciences 1990
ISBN: 9780203393284

doi:10.4324/9780203393284

Book

ABSTRACT

This issue comprises the twenty-five papers presented at the Second Music and the Cognitive Sciences conference held at Cambridge University in 1990.

Figure 3 Points: mean responses (26 data per point in part a, 52 in parts b– e). Bars: 95% confidence intervals. Squares: correlation coefficients between tone profiles according to (8), with k =4 and k=2.1, adjusted linearly to have the same mean and standard deviation as mean responses over all 60 values. In part e, the comparison chord is 047 (major triad)

chapter |9 pages

for the first three points 037 (minor triad) for the second three, 047Q (major-minor tetrad) for the third three, and 036Q (half-diminished tetrad) for the last three.

chapter |3 pages

Identification and blend of timbres as a basis for orchestration

chapter |1 pages

Figure 1 Illustration of one (a) and two (b) dimensional solutions for distances among three hypothetical stimulus points. Figure 2 Three dimensional solution for wind instrument dyad similarity ratings for Bd4–D5 major third context. Subjects were nonmusic

chapter |1 pages

majors. O=oboe, F=flute, T=trumpet, S=saxophone, C=clarinet. For example a pair is represented by letter combination: OF is oboe-flute. The second instrument was the soprano (D5).

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Figure 3 Two-dimensional INDSCAL solution summarizing wind instrument dyad distances across contexts. Left to right is “nasal” to “not nasal”; top to bottom is “rich” to “brilliant.” From Kendall & Carterette (1991).

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Figure 4 Two-dimensional configuration of single instruments positioned by a professor of musicology on the basis of mental image of timbre (Bb4). Dimension 1 (left to right) was “nasal” to “not nasal” and dimension 2 (top to bottom) was “rich” to “brilliant.” From Kendall & Carterette (1991).

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Figure 5 Rank order, from least to most, of mean blend (averaged over context) for the ten dyads.

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Figure 7 Rank order, from least to most, of mean correct identification (averaged over context) for the ten dyads.

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Figure 8 Classical multidimensional scaling solution for decomposed blend

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ratings. Stress was less than 0.00031 in two dimensions. Figure 8a is for unison and Figure 8b for noninverted-instrument major third contexts.

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Figure 9 Theoretically-derived dyad points from vector sums of the

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positions of instruments in Figure 8. Figure 9a is for unison and Figure 9b for noninverted-instrument major third contexts.

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What is the octave of a harmonically rich note?

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phase shifted 0–90 degrees. The central dashed diagonal in each subfigure shows the position of responses at the physical octave.

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(b) AAMP(9), (c) AAMP(18), (d) APH(60), (e) APH(90), and (f) AAMP(9)/APH(90). The attenuation and phase-shift manipulations introduce secondary peaks in the central portion of the period of the CPH wave.

chapter |1 pages

Figure 3 Auditory images of the sounds presented in Figure 2: (a) CPH, (b) AAMP(9), (c) AAMP(18), (d) APH(60), (e) APH(90), and (f) AAMP(9)/APH(90). The manipulations introduce activity into the central portion of the auditory

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image where the CPH image has no activity.

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Figure 4 Spiral excitation patterns extracted at 8 ms (lefthand column) and 4 ms (righthand column) from the

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auditory images in Figure 3: (a) CPH, (b) AAMP(9), (c) AAMP(18), (d) APH(90), and (f) AAMP(9)/ APH(90). Tone height increases when the similarity between the 8- and 4-ms patterns increases.

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Brightness and octave position: are changes in spectral envelope and in tone height perceptually equivalent?

chapter I|3 pages

The spectra depicted are the stimuli synthesized at Note C3.

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Figure 3 Spectra for the four sounds used in Experiment II. The top two spectra represent the steady-state brass stimuli synthesized at notes C4 and C3. The bottom two spectra represent the steady-state flute stimuli synthesized at notes C4 and C5.

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Figure 4 Instrument discrimination and pitch interval identification performance as a function of stimulus duration (Experiment II). TN and CF are musically untrained listeners, NR and KR musically trained listeners.

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Figure 5 Same instrument and unison interval judgments as a function of stimulus duration. TN and CF are musically untrained listeners, NR and KR musically trained listeners.

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Figure 6 Different instrument and octave interval judgments as a function of stimulus duration. TN and CF are musically untrained listeners, NR and KR musically trained listeners.

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Figure 1 Hierarchy of factors determining cognitively-mediated ear asymmetry.

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Figure 3 Cognitive operations involved in melody recall performance.

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Split-brain studies of music perception and cognition

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Figure 1 Magnetic resonance scans depicting lateral (a) and medial (b) views of the left cerebral hemisphere. These high-resolution images of the living brain, particularly in this plane

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(sagittal), became available to clinicians and brain scientists only in the last decade. In (a), the dotted line demarcates the temporal lobe (T); the top portion (superior surface) of the temporal lobe houses the auditory area in man. In (b), the arrows indicate the extent of the corpus callosum, the semilunar bundle of nerve fibers which connects the left and right hemispheres. In split-brain patients, the callosum is cut.

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Figure 2 Split-brain paradigm. The patient fixates a central point on a computer screen while the musical instrument sounds are played in free field. Since the visual pathways are normally crossed, when a picture is

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flashed in one visual field (here the picture of the violin is flashed in the left visual field), it is conveyed to the contralateral hemisphere (here the right hemisphere). In normal subjects, because of visual transfer across the corpus callosum, both hemispheres see the picture; in split-brain patients, no such transfer is possible, so only one hemisphere sees the picture. A tachistoscope is used to flash the picture for 150msec, faster than the eye can move, otherwise the picture might reach both hemispheres because of eye movements. A fast Fourier transform of the first 400msec of the violin sound is shown at the top of the figure [y axis=time in msec, x=kilohertz (kHz, or 1000cps), and height=relative amplitude (quantized sample value units)]. An example of one of the five melodic structures used to present the instrument sounds (here chromatic-variable) is also shown. In the next trial, a trumpet will play and a picture of a piano is flashed to the left hemisphere, and so on. (See text for further details of the experimental procedure).

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Figure 3 Bar graph illustrating the observed “double dissociation”: the left hemisphere was significantly more accurate than the right (p<.01) on the musical instrument timbre recognition task, while the right hemisphere performed significantly better than the left hemisphere on the Seashore Timbre Test (p<.05). For convenience, per cent accuracy is averaged across the two subjects, both of whom showed the same pattern of significant left-right differences (Tramo & Gazzaniga 1989, 1990).

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Figure 1 Schematic representation of the theory by Lerdahl 1989.

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Figure 4 Average profiles of musical tension obtained in the first experiment.

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Fig. 5 Effect of the implicit harmony in R1, R2, R3.

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Figure 6 Example of local interaction observed with musician subjects.

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Figure 8 Examples of the interaction between the tonal weight and the duration (short/long) observed on ending unit 7 (a), and between the tonal weight and the metrical position (weak/strong beat) observed on ending unit 12 (b) with musician subjects.

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Is the perception of melody governed by motivic arguments or by generative rules or by both?

chapter L|4 pages

—Santa Lucia; S—Scottish Lament. The order of the upper case symbols denotes the order of alternation while lower case symbols indicate the level of unitising: p—phrase; b—bar; n— note.

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Transformation, migration and restoration

Shades of illusion in the perception of music

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Figure 2 Real and apparent locus of clicks about a boundary [Melodic line in Condition 2].

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Associationism and musical soundtrack phenomena

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Figure 1 Mean sadness/happiness rating as a function of visual or auditory tempo (top panel) and of

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visual height or auditory pitch (bottom panel) for a bouncing ball and a simple melody, respectively. Figure 2 Mean sadness/happiness rating of the bouncing ball as a function of tempo of the bounce and a

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congruent or incongruent background melodic temporal pattern (top panel) and as a function of height of the bounce and congruent or incongruent background melodic pitch height (bottom panel). Figure 3 Schematic representation of a simple model of information integration from multiple visual and auditory dimensions which gives rise to the resultant meaning of the audio visual stimulus.

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characters as a function of the two contrasting musical soundtracks (Weak and Strong) and a condition with no soundtrack (Control). If there were no effect of background music, the data for the two music conditions would not differ from the Control conditions and all lines would be horizontal (Figure © 1988 by the Regents of the University of California, reprinted from Music Perception, Vol. 6, No. 1, Fall, p. 107, by permission.)

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selections, and for the combinations of music and film selections. Figure 6 Schematic representation of the simple associative model of meaning of film which integrates affective and denotative meanings from both musical and visual (scene) information from the film.

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Rhythm perception: Interactions between time and intensity

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Figure 2 Adjusted intervals in ms for target 2 (last short interval) as a function of the number of short intervals in the sequence (N), for the two starting values.

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Figure 3 Some hypotheses.

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Mechanisms of cue extraction in memory for musical time

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Figure 2a Boulez, Eclat: Perceived proximity of the extracts by musicians. Figure 2b Boulez, Eclat: Perceived proximity of extracts by non-musicians.

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Figure 3 Boulez, Eclat: Mean localisation judgement of extracts. Actual location of extracts x perceived location of extracts.

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of subjects it gives the mode, the mean localisation judgement observed and the displacement of this from the actual position.

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Generativity, mimesis and the human body in music performance

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musical performance (see text for details).

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Figure 2 The timing profile of an attempt to imitate an inverted version of one of the four melodies used in the imitation experiment (see text). Note the ‘cross over’ halfway through the performance, where the performer, having followed the inversion target quite closely, reverts to the timing profile of the original performance target.

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Figure 1 A ‘bars’ structure with part-of relation (a), its associated time intervals and constraints (b). Figure 2 A ‘progression’ structure with part-of relations (a), its associated time intervals and constraiants (b).

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A connectionist and a traditional AI quantizer, symbolic versus sub-symbolic models of rhythm perception

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Figure 2b Mapping in rhythm space in the traditional AI model

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Figure 3a Regions in rhythm space of the connectionist model Figure 3b Regions in rhythm space in the traditional AI model

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Figure 4a Influence of context (two dotted quarter notes) in the connectionist model

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Figure 4b Influence of context (duple meter) in the traditional AI model

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Figure 5a Influence of the peak parameter in the connectionist model

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Figure 5b Influence of the tolerance parameter in the traditional AI model

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Figure 6 Expectancy of onsets in the connectionist model

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Figure 7 Expectancy of onsets in different 2/4 contexts in the connectionist model Figure 8 Expectancy of onsets in 6/8 versus 3/4 rhythm in the connectionist model

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Figure 9 Expectancy of onsets in 2/4 context of the two models

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Computer perception of phrase structure

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Figure 2 Schubert, Arpeggione Sonata: pre-metrical grouping of durations. An asterisk denotes a phrase terminator, the grouping being the entire tree subtended from that level’s branches.

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Figure 6 Bach, Well-Tempered Clavier, Bk. 1; Fugue in F sharp minor.

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Figure 7 Haydn, Symphony No. 104. Added metrical information (thin-line brackets) is combined with compatible pre-metrical brackets (bold lines) to show the phrase structure in a metrical context.

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Figure 8 Chopin, Sonata in B minor. The opening two-bar phrase indicated by the top-level bracket is not found by the program and requires an analysis of the crotchet-level rhythm.

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Critical study of Sundberg’s rules for expression in the performance of melodies

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Contribution to the design of an expert system for the generation of tonal multiple counterpoint

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reversible counterpoint (by permission of Edizioni Kappa, Rome).

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outlined in the paper according to multiple viewpoints arranged in the following order of succession: “modal skeleton”, “tonalization”, “generation of the fourth voice” and “absolute pitch assignment”. The soprano line is a Bachian melody used also in Ebcioglu (1988). Figure 3 A modal example realised as follows: “modal skeleton”, fioriturae (figuration) and “absolute pitch assignment”. The cantus firmus has been drawn from Koechlin (1925).

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Figure 4 The over line procedure is preferred to the typical on line one: the solution-object is generated applying the competence viewpoints in successive moments, according to a given hierarchy (order of succession and weighting).

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Computer-aided comparison of syntax systems in three piano pieces by Debussy

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Figure 2 Pitch class simultaneity representation.

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Figure 4 Syntactic network for pitch class simultaneity representation of Chorale number 6.

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Figure 6 The sets, Tgenerated by the UniMap program for Chorale number 6.

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Figure 9 syntactic networks for three pieces by Debussy.

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A: Clair de lune B: Reflets dans l’eau C: Cloches à travers les feuilles XYZ: Centroids for function groups

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Figure 13 networks for “Clair” and “Reflets” and network for “Cloches”.

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Figure 14 Function graph for networks in Figure 13. A: Clair de lune B: Reflets dans l’eau C: Cloches à travers les feuilles ABC: Centroids of function groups

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Figure 16 Sum network for networks in Figure 15. Figure 17 Comparison of co-ordinates of ABC and XYZ centroids and best-fit networks.

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How do we perceive atonal music? Suggestions for a theoretical approach Michel IMBERTY

Music and the Cognitive Sciences 1990

ABSTRACT

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