Influences of acculturation and musical sophistication on perception of musical interval patterns

Time-course variation of statistics embedded in music: Corpus study on implicit learning and knowledge

Learning and knowledge of transitional probability in sequences like music, called statistical learning and knowledge, are considered implicit processes that occur without intention to learn and awareness of what one knows. This implicit statistical knowledge can be alternatively expressed via abstract medium such as musical melody, which suggests this knowledge is reflected in melodies written by a composer. This study investigates how statistics in music vary over a composer's lifetime. Transitional probabilities of highest-pitch sequences in Ludwig van Beethoven's Piano Sonata were calculated based on different hierarchical Markov models. Each interval pattern was ordered based on the sonata opus number. The transitional probabilities of sequential patterns that are musical universal in music gradually decreased, suggesting that time-course variations of statistics in music reflect time-course variations of a composer's statistical knowledge. This study sheds new light on novel methodologies that may be able to evaluate the time-course variation of composer's implicit knowledge using musical scores.

Expectations in culturally unfamiliar music: influences of proximal and distal cues and timbral characteristics

Listeners' musical perception is influenced by cues that can be stored in short-term memory (e.g., within the same musical piece) or long-term memory (e.g., based on one's own musical culture). The present study tested how these cues (referred to as, respectively, proximal and distal cues) influence the perception of music from an unfamiliar culture. Western listeners who were naïve to Gamelan music judged completeness and coherence for newly constructed melodies in the Balinese gamelan tradition. In these melodies, we manipulated the final tone with three possibilities: the original gong tone, an in-scale tone replacement or an out-of-scale tone replacement. We also manipulated the musical timbre employed in Gamelan pieces. We hypothesized that novice listeners are sensitive to out-of-scale changes, but not in-scale changes, and that this might be influenced by the more unfamiliar timbre created by Gamelan "sister" instruments whose harmonics beat with the harmonics of the other instrument, creating a timbrally "shimmering" sound. The results showed: (1) out-of-scale endings were judged less complete than original gong and in-scale endings; (2) for melodies played with "sister" instruments, in-scale endings were judged as less complete than original endings. Furthermore, melodies using the original scale tones were judged more coherent than melodies containing few or multiple tone replacements; melodies played on single instruments were judged more coherent than the same melodies played on sister instruments. Additionally, there is some indication of within-session statistical learning, with expectations for the initially-novel materials developing during the course of the experiment. The data suggest the influence of both distal cues (e.g., previously unfamiliar timbres) and proximal cues (within the same sequence and over the experimental session) on the perception of melodies from other cultural systems based on unfamiliar tunings and scale systems.

Melodic contour identification and music perception by cochlear implant users

Research and outcomes with cochlear implants (CIs) have revealed a dichotomy in the cues necessary for speech and music recognition. CI devices typically transmit 16-22 spectral channels, each modulated slowly in time. This coarse representation provides enough information to support speech understanding in quiet and rhythmic perception in music, but not enough to support speech understanding in noise or melody recognition. Melody recognition requires some capacity for complex pitch perception, which in turn depends strongly on access to spectral fine structure cues. Thus, temporal envelope cues are adequate for speech perception under optimal listening conditions, while spectral fine structure cues are needed for music perception. In this paper, we present recent experiments that directly measure CI users' melodic pitch perception using a melodic contour identification (MCI) task. While normal-hearing (NH) listeners' performance was consistently high across experiments, MCI performance was highly variable across CI users. CI users' MCI performance was significantly affected by instrument timbre, as well as by the presence of a competing instrument. In general, CI users had great difficulty extracting melodic pitch from complex stimuli. However, musically experienced CI users often performed as well as NH listeners, and MCI training in less-experienced subjects greatly improved performance. With fixed constraints on spectral resolution, such as occurs with hearing loss or an auditory prosthesis, training and experience can provide considerable improvements in music perception and appreciation.

Melodic contour identification by cochlear implant listeners

OBJECTIVE

While the cochlear implant provides many deaf patients with good speech understanding in quiet, music perception and appreciation with the cochlear implant remains a major challenge for most cochlear implant users. The present study investigated whether a closed-set melodic contour identification (MCI) task could be used to quantify cochlear implant users' ability to recognize musical melodies and whether MCI performance could be improved with moderate auditory training. The present study also compared MCI performance with familiar melody identification (FMI) performance, with and without MCI training.

METHODS

For the MCI task, test stimuli were melodic contours composed of 5 notes of equal duration whose frequencies corresponded to musical intervals. The interval between successive notes in each contour was varied between 1 and 5 semitones; the "root note" of the contours was also varied (A3, A4, and A5). Nine distinct musical patterns were generated for each interval and root note condition, resulting in a total of 135 musical contours. The identification of these melodic contours was measured in 11 cochlear implant users. FMI was also evaluated in the same subjects; recognition of 12 familiar melodies was tested with and without rhythm cues. MCI was also trained in 6 subjects, using custom software and melodic contours presented in a different frequency range from that used for testing.

RESULTS

Results showed that MCI recognition performance was highly variable among cochlear implant users, ranging from 14% to 91% correct. For most subjects, MCI performance improved as the number of semitones between successive notes was increased; performance was slightly lower for the A3 root note condition. Mean FMI performance was 58% correct when rhythm cues were preserved and 29% correct when rhythm cues were removed. Statistical analyses revealed no significant correlation between MCI performance and FMI performance (with or without rhythmic cues). However, MCI performance was significantly correlated with vowel recognition performance; FMI performance was not correlated with cochlear implant subjects' phoneme recognition performance. Preliminary results also showed that the MCI training improved all subjects' MCI performance; the improved MCI performance also generalized to improved FMI performance.

CONCLUSIONS

Preliminary data indicate that the closed-set MCI task is a viable approach toward quantifying an important component of cochlear implant users' music perception. The improvement in MCI performance and generalization to FMI performance with training suggests that MCI training may be useful for improving cochlear implant users' music perception and appreciation; such training may be necessary to properly evaluate patient performance, as acute measures may underestimate the amount of musical information transmitted by the cochlear implant device and received by cochlear implant listeners.

Maximum key-profile correlation (MKC) as a measure of tonal structure in music

Tonal structure is musical organization on the basis of pitch, in which pitches vary in importance and rate of occurrence according to their relationship to a tonal center. Experiment 1 evaluated the maximum key-profile correlation (MKC), a product of Krumhansl and Schmuckler's key-finding algorithm (Krumhansl, 1990), as a measure of tonal structure. The MKC is the maximum correlation coefficient between the pitch class distribution in a musical sample and key profiles, which indicate the stability of pitches with respect to particular tonal centers. The MKC values of melodies correlated strongly with listeners' ratings of tonal structure. To measure the influence of the temporal order of pitches on perceived tonal structure, three measures (fifth span, semitone span, and pitch contour) taken from previous studies of melody perception were also correlated with tonal structure ratings. None of the temporal measures correlated as strongly or as consistently with tonal structure ratings as did the MKC, and nor did combining them with the MKC improve prediction of tonal structure ratings. In Experiment 2, the MKC did not correlate with recognition memory of melodies. However, melodies with very low MKC values were recognized less accurately than melodies with very high MKC values. Although it does not incorporate temporal, rhythmic, or harmonic factors that may influence perceived tonal structure, the MKC can be interpreted as a measure of tonal structure, at least for brief melodies.

Responsiveness of Western adults to pitch-distributional information in melodic sequences

Responsiveness of musically trained and untrained adults to pitch-distributional information in melodic contexts was assessed. In Experiment 1, melodic contexts were pure-tone sequences, generated from either a diatonic or one of four nondiatonic tonesets, in which pitch-distributional information was manipulated by variation of the relative frequency of occurrence of tones from the toneset. Both the assignment of relative frequency of occurrence to tones and the construction of the (fixed) temporal order of tones within the sequences contravened the conventions of western tonal music. A probe-tone technique was employed. Each presentation of a sequence was followed by a probe tone, one of the 12 chromatic notes within the octave. Listeners rated the goodness of musical fit of the probe tone to the sequence. Probe-tone ratings were significantly related to frequency of occurrence of the probe tone in the sequence for both trained and untrained listeners. In addition, probe-tone ratings decreased as the pitch distance between the probe tone and the final tone of the sequence increased. For musically trained listeners, probe-tone ratings for diatonic sequences tended also to reflect the influence of an internalized tonal schema. Experiment 2 demonstrated that the temporal location of tones in the sequences could not alone account for the effect of frequency of occurrence in Experiment 1. Experiment 3 tested musically untrained listeners under the conditions of Experiment 1, with the exception that the temporal order of tones in each sequence was randomized across trials. The effect of frequency of occurrence found in Experiment 1 was replicated and strengthened.