I n a study of tempo perception , L ondon , Burger, Thompson, and Toiviainen (2016) presented participants with digitally ‘‘tempo-shifted’’ R&B songs (i.e., sped up or slowed down without otherwise altering their pitch or timbre). They found that while participants’ relative tempo judgments of original versus altered versions were correct, they no longer corresponded to the beat rate of each stimulus. Here we report on three experiments that further probe the relation(s) between beat rate, tempo-shifting, beat salience, melodic structure, and perceived tempo. Experiment 1 is a replication of London et al. (2016) using the original stimuli. Experiment 2 replaces the Motown stimuli with disco music, which has higher beat salience. Experiment 3 uses looped drum patterns, eliminating pitch and other cues from the stimuli and maximizing beat salience. The effect of London et al. (2016) was replicated in Experiment 1 , present to a lesser degree in Experiment 2 , and absent in Experiment 3 . Experiments 2 and 3 also found that participants were able to make tempo judgments in accordance with BPM rates for stimuli that were not tempo-shifted. The roles of beat salience, melodic structure, and memory for tempo are discussed, and the TAE as an example of perceptual sharpening is considered.

T he current study explores how individuals ' tendency to empathize with others (trait empathy) modulates interaction and social entrainment in dyadic dance in a free movement context using perceptual and computationally derived measures. Stimuli consisting of 24 point-light animations were created using motion capture data selected from a sample of 99 dyads, based on self-reported trait empathy. Individuals whose Empathy Quotient (EQ) scores were in the top or bottom quartile of all scores were considered to have high or low empathy, respectively, and twelve dyads comprised of four high-high, four low-low, and four high-low empathy combinations were identified. Animations of these dyads were presented to 33 participants, who rated the degree of interaction and movement similarity for each stimulus. Results showed a significant effect of empathy combination on perceived interactivity and perceived similarity. High-low stimuli were rated as significantly more interactive than either high-high or low-low stimuli, while high-high stimuli were rated as significantly less similar than high-low and low-low. Dyads’ period-locking, bodily orientation and amount of hand movement were all significantly correlated with rated amount of interaction, while rated similarity only related significantly to period-locking. Results suggest that period-locking is important for social entrainment to be perceived, but that other signals such as bodily orientation and hand movement also signal social entrainment during free dance movement.

While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects of experimental task (i.e., real-time vs. annotated segmentation), nor of musicianship on boundary perception are clear. Our study assesses musicianship effects and differences between segmentation tasks. We conducted a real-time experiment to collect segmentations by musicians and nonmusicians from nine musical pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary indication density, although this might be contingent on stimuli and other factors. In line with other studies, no musicianship effects were found: our results showed high agreement between groups and similar inter-subject correlations. Also consistent with previous work, time scales between one and two seconds were optimal for combining boundary indications. In addition, we found effects of task on number of indications, and a time lag between tasks dependent on beat length. Also, the optimal time scale for combining responses increased when the pulse clarity or event density decreased. Implications for future segmentation studies are raised concerning the selection of time scales for modelling boundary density, and time alignment between models.

What is the effect of performers’ experienced emotions on the auditory characteristics of their performances? By asking performers to play a music phrase in response to three different instructions we attempted to answer this question. Performers were instructed to do the following: 1) play while focusing on the technical aspects of their playing; 2) give an expressive performance; and 3) focus on their experienced emotions, prior to which they were subjected to a sadness-inducing mood induction task. Performers were interviewed after each playing condition. We analyzed the tempo, articulation, dynamics, timbre, and vibrato of the performances obtained as well as the interview data. A focus on technique resulted in technically appropriate performances, a focus on expressivity in more extraverted and externally projected performances, and a focus on experienced emotions in more introverted and personal performances. The findings of this exploratory study are valuable for both research and artistic practice and pedagogy.

Listening to music makes us move in various ways. Several factors can affect the characteristics of these movements, including individual factors and musical features. Additionally, music-induced movement may also be shaped by the emotional content of the music, since emotions are an important element of musical expression. This study investigates possible relationships between emotional characteristics of music and music-induced, quasi-spontaneous movement. We recorded music-induced movement of 60 individuals, and computationally extracted features from the movement data. Additionally, the emotional content of the stimuli was assessed in a perceptual experiment. A subsequent correlational analysis revealed characteristic movement features for each emotion, suggesting that the body reflects emotional qualities of music. The results show similarities to movements of professional musicians and dancers, and to emotion-specific nonverbal behavior in general, and could furthermore be linked to notions of embodied music cognition. The valence and arousal ratings were subsequently projected onto polar coordinates to further investigate connections between the emotions of Russell’s (1980) circumplex models and the movement features

polyphonic timbre perception was investigated in a cross-cultural context wherein Indian and Western nonmusicians rated short Indian and Western popular music excerpts (1.5 s, n = 200) on eight bipolar scales. Intrinsic dimensionality estimation revealed a higher number of perceptual dimensions in the timbre space for music from one's own culture. Factor analyses of Indian and Western participants' ratings resulted in highly similar factor solutions. The acoustic features that predicted the perceptual dimensions were similar across the two participant groups. Furthermore, both the perceptual dimensions and their acoustic correlates matched closely with the results of a previous study performed using Western musicians as participants. Regression analyses revealed relatively well performing models for the perceptual dimensions. The models displayed relatively high cross-validation performance. The findings suggest the presence of universal patterns in polyphonic timbre perception while demonstrating the increase of dimensionality of timbre space as a result of enculturation.

The visual channel has been shown to be more informative than the auditory channel in perceptual judgments of a performer's level of expression. Previous work has revealed a positive relationship between amplitude of music-related movement and ratings of expression, for example, and observers have been shown to be sensitive to kinematic features of music-related movement. In this study, we investigate relationships between the kinematics of a conductors' expressive gestures and ratings of perceived expression. Point-light representations (totalling 10 minutes) of two professional conductors were presented to participants who provided continuous ratings of perceived valence, activity, power, and overall expression using a virtual slider interface. Relationships between these ratings and 11 kinematic variables computationally extracted from the movement data were subsequently examined using linear regression. Higher levels of expressivity were found to be conveyed by gestures characterized by increased amplitude, greater variance, and higher speed of movement.

Listening to music often is associated with spontaneous body movements frequently synchronized with its periodic structure. The notion of embodied cognition assumes that intelligent behavior does not emerge from mere passive perception, but requires goal-directed interactions between the organism and its environment. According to this view, one could postulate that we may use our bodily movements to help parse the metric structure of music. The aim of this study was to investigate how pulsations on different metrical levels manifest in music-induced movement. Musicians were presented with a piece of instrumental music in 4/4 time, played at four different tempi ranging from 92 to 138 bpm. Participants were instructed to move to the music, and their movements were recorded with a high quality optical motion capture system. Subsequently, signal processing methods and principal components analysis were applied to extract movement primitives synchronized with different metrical levels. We found differences between metric levels in terms of the prevalence of synchronized eigenmovements. For instance, mediolateral movements of arms were found to be frequently synchronized with the tactus level pulse, while rotation and lateral flexion of the upper torso were commonly found to exhibit periods of two and four beats, respectively. The results imply that periodicities on several metric levels are simultaneously present in music-induced movement. This could suggest that the metric structure of music is encoded in these movements.

POLYPHONIC TIMBRE HAS BEEN DEMONSTRATED TO BE an important element for computational categorization according to genre, style, mood, and emotions, but its perceptual constituents have received less attention. The work presented here comprises two experiments, Experiment 1, to devise a framework of subjective rating scales for quantifying the perceptual qualities of polyphonic timbre and Experiment 2, to rate short excerpts of Indian popular music and correlate them with computationally extracted acoustic features. A factor analysis of the ratings suggested three perceptual dimensions: Activity, Brightness, and Fullness. The present findings imply that there may be regularities and patterns in the way people perceive polyphonic timbre. Furthermore, the perceptual dimensions can be predicted relatively well by the regression models. Spectrotemporal modulations were found to be most relevant, while the well known polyphonic timbre descriptors, the Mel-Frequency Cepstral Coefficients, did not contribute significantly to any of the perceptual dimensions.

Previous work suggests that the perception of a visual beat in conductors’ gestures is related to certain physical characteristics of the movements they produce, most notably to periods of negative acceleration, and low position in the vertical axis. These findings are based on studies that have presented participants with somewhat simple gestures, and in which participants have been required to simply tap in time with the beat. Thus, it is not clear how generalizable these findings are to real-world conducting situations, in which a conductor uses considerably more complex gestures to direct an ensemble of musicians playing actual instruments. The aims of the present study were to examine the features of conductors’ gestures with which ensemble musicians synchronize their performance in an ecologically valid setting and to develop automatic feature extraction methods for the analysis of audio and movement data. An optical motion capture system was used to record the gestures of an expert conductor directing an ensemble of expert musicians over a 20-minute period. A simultaneous audio recording of the performance of the ensemble was also made and synchronized with the motion capture data. Four short excerpts were selected for analysis, two in which the conductor communicated the beat with high clarity, and two in which the beat was communicated with low clarity. Twelve movement variables were computationally extracted from the movement data and cross-correlated with the pulse of the ensemble’s performance, the latter based on the spectral flux of the audio signal. Results of the analysis indicated that the ensemble’s performance tended to be most highly synchronized with periods of maximal deceleration along the trajectory, followed by periods of high vertical velocity (a higher correlation than deceleration but a longer delay).

We studied the process of pulse finding by using mechanical performances of composed music in which it is fairly challenging to find a pulse. Human participants synchronized to short musical excerpts that varied in the amount of musical information present, the amount of syncopation, and the metrical position of the first note. We quantified the period and phase of tapping, the amount of nonsynchronized tapping, the time to start tapping, the variability of the intertap interval, and the deviation of taps from the intended musical events. The amount of musical information and the amount of syncopation were predictors of pulse-finding ability (metrical appropriateness of tapping, time to start tapping, variability of tapping, and deviations from the beat), and the metrical position of the first note of excerpts biased participants to tap with the corresponding phase. In addition, the degree to which participants tapped in consensus correlated positively with pulse-finding ability. We modeled participants' behavior by using a resonance equation to calculate the strength of all metrically appropriate periodicities. The summed activation strength across the periodicities correlated with pulse-finding ability. Our results demonstrate that musical pulse finding is a useful behavioral paradigm for modeling the influences of stimulus features on complex sensorimo-tor synchronization.

Listeners are sensitive to pitch distributional information in music (N. Oram & L. L. Cuddy, 1995; C. L. Krumhansl, J. Louhivuori, P.Toiviainen, T. Jäärvinen, & T. Eerola, 1999). However, it is uncertain whether frequency-based musical features are sufficient to explain the similarity judgments that underlie listeners' classification processes. A similarity rating experiment was designed to determine the effectiveness of these features in predicting listeners' similarity ratings. The material consisted of 15 melodies representing five folk music styles. A multiple regression analysis showed that the similarity of frequency-based musical properties could account for a moderate amount (40%%) of listeners' similarity ratings. A slightly better predictive rate (55%%) was achieved by using descriptive variables such as number of tones, rhythmic variability, and melodic predictability. The results suggest that both measures were able to capture some aspects of the structures that portray common salient dimensions to which listeners pay attention while categorizing melodies. Aikaisemmissa tutkimuksissa on osoitettu, ettää musiikin tilastollisilla tapahtumilla, kuten säävelten määäärillää ja tyypillisillää intervalleilla, on merkitystää, kun kuulijat muodostavat kääsityksiääään musiikin rakenteesta (N. Oram & L. L. Cuddy, 1995; C. L. Krumhansl, J. Louhivuori, P. Toiviainen, T. Jäärvinen, & T. Eerola, 1999). Nääiden piirteiden voidaan olettaa olevan täärkeitää myöös musiikin luokittelussa. Toistaiseksi ei kuitenkaan tiedetää, miten hyvin tilastollisilla piirteillää voitaisiin musiikin luokittelua selittääää. Täätää testattiin kuulijoille jäärjestetyn samanlaisuusarviointitehtäävään avulla. Tutkimuksen materiaali koostui 15 melodiasta, jotka edustivat viittää eri kansanmusiikkityyliää. Regressioanalyysi paljasti, ettää musiikin tilastollisten piirteiden samanlaisuus pystyi selittäämääään kohtuullisen määäärään (40%%) kuulijoiden antamista samanlaisuusarvioista. Hieman parempi selitysaste (55%%) saavutettiin kuvaavilla muuttujilla, joita olivat melodian laajuus ja ennakoitavuus sekää rytmin vaihtelevuus. Nääin ollen tulokset antavat aiheen olettaa, ettää musiikin tilastolliset piirteet ja kuvailevat muuttujat vaikuttavat kuulijoiden luokittelupäääätööksiin.

This study of Finnish spiritual folk hymns combined three approaches to understanding melodic expectation. The first approach was a statistical style analysis of a representative corpus of 18 hymns, which determined the relative frequencies of tone onsets and two- and three-tone transitions. The second approach was a behavioral experiment in which listeners, either familiar (experts) or unfamiliar (nonexperts) with the hymns, made judgments about melodic continuations. The third approach simulated melodic expectation with neural network models of the self-organizing map (SOM) type (Kohonen, 1997). One model was trained on a corpus of Finnish folk songs and Lutheran hymns (Finnish SOM), while another was trained with the hymn contexts used in the experiment with the correct continuation tone (Hymn SOM). The three approaches converged on the following conclusions: (1) Listeners appear to be sensitive to the distributions of tones and tone transitions in music, (2) The nonexperts' responses more strongly reflected the general distribution of tones, whereas the experts' responses more strongly reflected the tone transitions and the correct continuations, (3) The SOMs produced results similar to listeners and also appeared sensitive to the distributions of tones and tone transitions, (4) The Hymn SOM correlated more strongly with the experts' judgments than the Finnish SOM, and (5) the principles of the implication-realization model (Narmour, 1990) were weighted similarly by the behavioral data and the Hymn SOM. /// Tässä suomalaisia hengellisiä kansansävelmiä käsittelevässä tutkimuksessa pyrittiin selvittämään melodisia odotuksia kolmen tutkimusmenetelmän avulla. Ensimmäinen menetelmä oli kyseistä tyyliä edustavien 18 sävelmän tilastollinen analyysi, jossa määritelteltiin sävelkorkeuksien sekä kahden ja kolmen sävelen siirtymien tilastolliset jakaumat. Toinen menetelmä oli behavioraalinen koe, jossa kuulijat arvioivat sävelmien jatkoja. Kuulijat jakaantuivat kahteen ryhmään: sävelmät tunteviin (asiantuntijoihin) ja sävelmiä tuntemattomiin (ei-asiantuntijoihin). Kolmannessa menetelmässä simuloitiin melodisia odotuksia itsejärjestäytyvään karttaan (Kohonen, 1997) perustuvalla keinotekoisella hermoverkkomallilla. Ensimmäiselle mallille opetettiin joukko suomalaisia kansanlauluja ja luterilaisia virsiä (suomalainen verkko), toiselle kokeessa käytettyjä hengellisiä kansansävelmiä (hengellinen verkko). Käytetyt menetelmät tuottivat yhteneviä tuloksia ja antoivat aihetta seuraaviin johtopäätöksiin: (1) kuulijat näyttävät olevan vastaanottavaisia musiikin säveljakaumille ja sävelsiirtymille, (2) ei-asiantuntijoiden vastaukset noudattivat enemmän sävelten yleistä jakaumaa, kun taas asiantuntijoiden vastaukset heijastivat enemmän sävelsiirtymiä ja sävelmien oikeita jatkoja, (3) hermoverkot tuottivat tuloksia, jotka olivat samankaltaisia kuulijoiden arvioiden kanssa ja jotka noudattivat sävelten ja sävelsiirtymien jakaumia, (4) hengellisen verkon tulokset korreloivat suomalaisen verkon tuloksia voimakkaammin asiantuntijoiden arvioiden kanssa, ja (5) behavioraaliset tulokset ja hengellinen verkko painottavat implikaatio-realisaatio-mallin (Narmour, 1990) periaatteita samalla tavalla.

The present study compared the degree of similarity of timbre representations as observed with brain recordings, behavioral studies, and computer simulations. To this end, the electrical brain activity of subjects was recorded while they were repetitively presented with five sounds differing in timbre. Subjects read simultaneously so that their attention was not focused on the sounds. The brain activity was quantified in terms of a change-specific mismatch negativity component. Thereafter, the subjects were asked to judge the similarity of all pairs along a five-step scale. A computer simulation was made by first training a Kohonen self-organizing map with a large set of instrumental sounds. The map was then tested with the experimental stimuli, and the distance between the most active artificial neurons was measured. The results of these methods were highly similar, suggesting that timbre representations reflected in behavioral measures correspond to neural activity, both as measured directly and as simulated in self-organizing neural network models.

In cognitive science and research on artificial intelligence, there are two central paradigms: symbolic and analogical. Within the analogical paradigm, artificial neural networks (ANNs) have recently been successfully used to model and simulate cognitive phenomena. One of the most prominent features of ANNs is their ability to learn by example and, to a certain extent, generalize what they have learned. Improvisation, the art of spontaneously creating music while playing or singing, fundamentally has an imitative nature. Regardless of how much one studies and analyzes, the art of improvisation is learned mostly by example. Instead of memorizing explicit rules, the student mimics the playing of other musicians. This kind of learning procedure cannot be easily modeled with rule- based symbolic systems. ANNs, on the other hand, provide an effective means of modeling and simulating this kind of imitative learning. In this article, a model of jazz improvisation that is based on supervised learning ANNs is described. Some results, achieved by simulations with the model, are presented. The simulations show that the model is able to apply the material it has learned in a new context. It can even create new melodic patterns based on the learned patterns. This kind of adaptability is a direct consequence of the fact that the knowledge resides in a distributed form in the network.