Guide The Basis of Music

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Increased expertise is associated with an enhanced ability to hold a specific pitch in mind through a period of silence [18] and mentally compare pitches corresponding to lyrics in familiar songs [17] , [19]. It is also associated with an enhanced ability to maintain accurate pitch and tempo in mentally continuing musical sequences following a short, sounded introduction [16].

If expert musicians imagine pitch and time more accurately than do novices, they may imagine other parameters, including loudness, more accurately too. Expertise is characterised by a maximisation of efficiency in the processing networks underlying performance on a specific set of tasks [33]. In the Western classical music tradition, performance expertise requires both technical and expressive mastery [12] , [34]. Technical demands involve coordinating sequences of movements within a narrow margin of error, often at a rapid pace [34].

Technical proficiency lays the groundwork for musical expression, the systematic deviation from and addition of such features as loudness to the fixed pitch and time structure that distinguishes one piece of music from another, reflecting a specific interpretation of that music. Expression is one component of what can give music its aesthetic [35] , emotional [36] and communicative qualities [36] , [37]. Expert musicians are distinguished from non-experts by their ability to replicate their own expressive performances at will with near-perfect precision or, with little or no practice, alter their interpretation to produce an entirely different expressive profile [9].

Imagining familiar music involves a process of reconstruction. Prior knowledge of musical structure within the relevant musical tradition can support the veridical retention of some details and fill in where other details have been lost. Experts demonstrate superior memory for domain-relevant stimuli relative to novices, perhaps because they organise material in memory more effectively [12] , [38].

Williamon and Valentine [13] observed differences in how highly-skilled musicians and novices structure memory while preparing a piece of music for performance. All musicians segmented the music during practice and performance, regularly stopping and starting at particular locations; these segments were understood to correspond to retrieval structures that participants were storing in memory. While novices often stopped and started at bars they found difficult, retrieval structures used by highly-skilled musicians tended to be hierarchical and corresponded more to formal music structure e.

Expressive loudness changes tend to relate predictably to specific structural features in the Western classical music tradition [6] , [9] , [36] , such as phrase boundaries, and may be more likely to be imagined if reconstructed from a memory trace that preserves this underlying structural detail than if reconstructed from a memory trace that does not. There is evidence to suggest that even non-musicians understand musical structure to a high degree, despite lacking the vocabulary needed to put their knowledge into words and the technical skills necessary to demonstrate it on music performance tasks.

When imagining familiar music, for instance, non-musicians imagine sections, or chunks, that correspond to the underlying musical structure [39]. Non-musicians likewise differ little from skilled musicians in their ability to use implicit knowledge of structure when listening to music [40]. In the present study, it was hypothesised that expressive loudness change can be imagined, and that the veridicality of this imagery improves with increasing musical expertise.

In the design of any task used to assess the relationship between musical imagery ability and expertise, the skills musicians have refined explicitly through years of practice and training need to be taken into account. Abilities such as working memory span and music listening ability, or how closely a person can attend to sounded music, likely contribute to success on musical imagery tasks and should be taken into consideration. The veridicality of imagery for familiar music depends, in part, on the strength of the memory trace from which it was reconstructed and, consequently, how effectively the music was encoded at the time it was sounded.

This points to a potential correlation between musical imagery and listening abilities: a person who attends more closely to music while listening and encodes more detail may have a more veridical musical image than a person who attends less closely and encodes less detail. The relationships between attention paid while listening, detail encoded, and veridicality of imagery are not guaranteed, as it is possible to imagine detail that was not encoded and to perceive and attend to detail in sounded music without encoding it.

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To avoid confounding the capacity to imagine music with the attention paid while listening and the detail encoded, listening ability was assessed in the present study to determine whether it could account entirely for performance on the imagery task. The veridicality of imagined music may also depend on working memory capacity.

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The working memory system permits temporary storage and manipulation of information and is said to mediate mental imagery [45] , [46]. Whether musical expertise is associated with improvements in such general cognitive abilities as working memory is a question of interest in the musical expertise literature [47] , [48] , [49]. The relationship between musical expertise and general working memory capacity is unclear, however.

Theoretical accounts of expertise posit that more effective structuring of domain-relevant material in working memory, rather than greater general working memory capacity, enables experts to reliably outperform novices [38] , [50]. While some researchers in the music domain have found expert and novice musicians to perform similarly on tasks assessing working memory capacity [48] , [49] , others have observed a greater verbal working memory capacity in trained musicians relative to non-musicians [47] In the present study, working memory span was also assessed to ensure that general memory abilities i.

Musicians stress that it is important to be able to imagine the desired effects of their actions in order to produce them [51] , implying that those who are better at performing music are likewise better at imagining it. Some research, also, suggests that musical imagery may partially compensate and enable performance or mental rehearsal in the absence of auditory or motor feedback [52] , [53] , [54].

Repp [23] found that skilled pianists only slightly attenuate their performance of expressive loudness, measured in terms of key velocity, when playing on a silent keyboard, compared to their performance under normal conditions. If expert musicians can imagine loudness, are they better able to do so than novice musicians and non-musicians? The present study investigated the abilities of expert musicians, novice musicians, and non-musicians to imagine loudness in well-known classical music.

Participants were grouped according to their scores on the Ollen Musical Sophistication Index OMSI [55] , [56] , which categorises people as more or less musically sophisticated based on such factors as amount and level of formal training, composition experience, and practice and music listening habits. In most previous research on musical expertise, comparisons have been made between either expert and novice performers, or between musicians and non-musicians. Three skill groups, in contrast, were included in the present study to investigate the possibility that expertise groups differ asymmetrically in terms of imagery ability.

Some musical skills, such as knowledge of how to read music notation, may develop earlier than other skills, such as the ability to communicate expression, in people learning to play an instrument. Imagery ability may be among those skills that develop early in the course of musical training, in which case novices would perform more like experts on imagery tasks than like non-musicians. Alternatively, imagery ability may be among those skills that develop later, in which case novices would perform more like non-musicians than experts. Based on evidence that expert musicians imagine pitch and duration more accurately than novices or non-musicians [16] , [18] , [19] and organise musical information more effectively in memory [13] , [57] , [58] , it was hypothesised that the veridicality with which loudness change can be imagined would increase as a function of musical expertise.

Participants imagined short passages of well-known classical music while, in one condition, tapping out the rhythm, and in the other, adjusting a slider to indicate imagined loudness. Similarity between participant response profiles and original recording profiles was expected to increase as a function of expertise.

Both loudness and tapping conditions were then repeated while participants listened to the same passages, so that listening ability could be assessed. Tapping data were collected and used as preliminary evidence that participants had recalled the correct passages of music. Written informed consent was obtained from all participants, and the study was approved by the University of Western Sydney Human Research Ethics Committee Approval number H Fifty-eight participants from a variety of musical backgrounds took part in the experiment.

A subset were musically-untrained psychology students at the University of Western Sydney UWS ; the remainder had at least one year of formal music training and included students at UWS, the Sydney Conservatorium of Music, and University of Canberra, as well as professional musicians in the Greater Sydney area. Tertiles were calculated for the distribution of participant scores on the OMSI and these values were used to categorise the participants who met inclusion criteria for each stimulus see Analysis into three expertise groups.

The novice group was older on average than either of the non-musician or expert musician groups. Age did not correlate significantly with any of the dependent measures, however, suggesting that age-related differences could not account for the results. Musically-trained participants had studied one or more of a range of instruments, including flute, guitar, piano, trumpet, viola, violin, and voice. Psychology students at UWS received course credit for their participation; all others received a small travel reimbursement.

All data for two additional participants were lost due to equipment failure. Loudness data for a third participant were also lost due to equipment failure, but timing data were retained and analysed. One excerpt was taken from each of three well-known pieces of Romantic-style orchestral music Blue Danube Waltz , Habanera , and Jupiter. These pieces were selected from a larger pool based on a preliminary familiarity survey as well as length, the absence of lyrics, degree of dynamic variability, degree of rubato expressive timing deviations , and the presence of an easily tapped melodic rhythm.

The passage from Jupiter was used as practice, and the passages from the Blue Danube Waltz and Habanera were used on experimental trials. The length and acoustic intensity range of the passages are reported in Table 1. MP3 files for each stimulus were imported into Audacity and converted to. The chosen passages were isolated and fades added where necessary to ensure that passages began and ended cleanly on phrase boundaries. Intensity profiles of the reference recordings dB SPL were measured using the acoustic analysis software Praat. To establish note onset profiles, a time series of melody line interonset intervals IOIs was generated using SonicVisualiser.

Procrustes analysis is used to calculate the degree of fit between two shapes with the effects of translation, scaling and rotation removed. The closer P is to zero, the better the fit is between the two data series, with 1— P being comparable to R [60] , [61]. The slider mm in length was fixed to a plastic box that inclined away from the participant. Upwards movement, or movement away from the participant, indicated an increase in loudness, and downwards movement, or movement towards the participant, indicated a decrease in loudness.

The top position represented the loudest point in the piece and the bottom position silence. A three-factor mixed model design was used, with expertise group acting as a between-subjects independent variable and task imagery or listening and condition loudness or tapping acting as within-subject independent variables. The first phase of the experiment was designed to ensure that all participants were familiar with the same version of each well-known music stimulus and able to recall the passages.

They were told that this was a minimum and encouraged to listen to the CD as many times as they wanted during this period. Participants were told that the experiment was part of a study on familiarity and enjoyment of music. They were to rate liking and familiarity of each passage on 5-point scales each time they listened to it. The topic and aims of the experiment were withheld to prevent participants from selectively attending to specific parameters in the music or attempting to memorise it.

Participants came to the laboratory for the second phase of the experiment one day after completing their final listening assignment. They received general instructions, completed a musical background questionnaire including all questions from the OMSI , and were asked to rate their familiarity with each stimulus.

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The imagery tasks were always completed before the listening tasks. Loudness and tapping trials were blocked separately within each task, with half the participants completing the loudness task first and half the tapping task. The order of passage presentation was randomised for each participant, irrespective of expertise group, within each of the four conditions. Participants completed the loudness and tapping tasks once for each passage under imagery conditions and once more for each passage under listening conditions, for a total of 24 trials i.

At the start of each condition, participants received specific instructions about how to complete the task. As it was expected that non-musicians would have little or no experience in singling out individual parameters of music, such as loudness or timing, instructions for how to tap a rhythm and map out loudness were explained in detail.

Participants were told to match tapping speed to changes in the speed of the music and, similarly, to match slider movements to speed, direction and degree of loudness change. Written and oral instructions were provided and were followed by a demonstration and practice trial with oral feedback from the experimenter to ensure that participants understood the task.

When you indicate that you are ready to start, a few seconds of music will play, then rapidly fade to silence. As soon as you hear the music, adjust the slider to indicate the level of loudness you are hearing. Try to imagine the music at the speed you are used to hearing it. Focus on hearing the music as clearly as possible in your head. Do not sing or hum the music aloud. During tapping condition practice trials, participants received visual feedback with the onset of each tap in the form of a blinking light on the computer screen so that they understood how much force was needed for the drumpad to detect their taps.

This visual feedback was not given during the experimental trials. Participants were not instructed to relate the force of their tapping to the loudness of the sounded or imagined music, and tapping force was not recorded. The use of vocabulary that could be understood differently by musicians and non-musicians e. In the loudness condition, brief instructions were presented on screen.

Participants indicated that they were ready to begin the first trial by clicking the mouse on a start button. Two seconds later, a passage cue consisting of the first few seconds of the excerpt fading into silence was presented through their headphones mean cue length 3.

The volume was pre-set to a comfortable level, but participants were free to adjust it if they wished. The task was to map out changes in loudness of the imagined music by continuously adjusting the position of the slider. Participants began each trial with the slider in the bottom silent position, and were to adjust it as quickly as possible to match the loudness of the music they were hearing.

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When the cue faded out a few seconds later, they were to keep adjusting slider position to indicate the loudness changes in the imagined continuation of the passage. They were told to keep their hand on the slider at all times.

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A visual signal indicated the end of the trial; participants were told that this meant that they should be finished or almost finished imagining the passage. Along with the brief instructions that remained on the screen throughout the condition, this was the only visual information given. Participants were then allowed a short break and again indicated by clicking the mouse button when they were ready to begin the next trial.

A similar procedure was used in the tapping condition. Participants indicated when they were ready to begin, and two seconds later a cue was presented. The task was to tap out the rhythm of the main melody for the passage on the drumpad. Using the index or middle finger of their dominant hand, participants were to begin tapping as soon as possible after the cue began. When the music faded out, they were to keep tapping the melody while imagining the continuation of the passage. Again, a visual signal indicated the end of each trial, at which point participants were allowed a short break and indicated that they were ready to continue by clicking the mouse button.

The experimenter remained in the room during testing to ensure that participants were not engaging in any unwanted production behaviour, such as vocalising the music. They were likewise cautioned against guessing, skipping sections or starting over mid-trial and, instead, were told to press a key to end a trial if they got lost or distracted while imagining the passage. As in the imagery task, brief instructions remained on the computer screen throughout each condition.

Participants indicated when they were ready to begin by clicking the mouse on a start button, and two seconds later the music began. Instead of fading out after a few seconds, however, passages were played in their entirety. The task in the loudness condition was again to map out the loudness changes in the passage by continuously adjusting the slider.

Participants began each trial with the slider in the bottom silent position and, when the music began playing, were to adjust it as quickly as possible to match loudness of the music they were hearing. They continued adjusting the slider until the passage concluded and a visual signal indicated the end of the trial, at which point they were allowed a short break before continuing. The task in the tapping condition was again to tap out the rhythm of the main melody for each passage.

Participants were to begin tapping the rhythm as soon as possible after the music began, and continue tapping throughout the duration of the trial. When the passage concluded, a visual signal indicated the end of the trial, just as in the imagery task, and participants were again allowed a short break before continuing.

An automated version of the Operation Span Task designed by Turner and Engle [59] was used to assess working memory. This task was selected from among the various available measures of working memory span on the basis of its high validity and reliability [62] and because it relies less than other measures on language abilities, which may also vary systematically as a function of musical expertise [63]. Participants received instructions and practice trials on the computer.

During the task, equations containing two operations were presented in the centre of the computer screen e. Participants indicated that they had mentally solved the equation by clicking the mouse button. An upper-case letter was then displayed for one second in the centre of the screen. All numbers and letters were presented in a sans-serif font and the same font size measuring. They were informed that after each set of between two and seven equations, they would be asked to recall the letters in the order they were presented. No access to pen and paper or other aids was permitted.

It was hypothesised that participants in all expertise groups would be able to imagine the loudness of the passages, but that experts would imagine it more veridically than would either novices or non-musicians. Acoustic intensity was used as a reference in the current study because it has been shown to be the primary contributor to perceived loudness [3]. Table 2 lists the dependent variables and their definitions.

These comparisons were made using time series analysis and dynamic time warping, as data points within profiles were not independent and correlations would have been uninformative. The three dependent variables and potential covariate measures of listening ability and working memory span then were examined to investigate the expected effects of expertise.

Because the passages were long, participants were not always able to remember them in their entirety. The first stage of analysis, therefore, involved identifying participant profiles that corresponded to accurately recalled music so that this subset of participant data could be assessed for image veridicality. Dynamic time warping DTW was used to assess the accuracy of imagined tapping profiles, or their similarity to reference note onset profiles, as well as their length see Appendix S1.

Tapping profiles were composed of the series of IOIs between each tap. An original aim of the study had been to investigate imagery for expressive timing as well as loudness. However, the great difficulty many participants had in tapping out rhythms under both imagery and listening conditions meant that neither perceived nor imagined expressive timing could be meaningfully assessed. Tapping data are therefore only presented as the basis for a decision to retain or exclude participant loudness profiles. Rated loudness is subjective and a function of multiple acoustic parameters [4] , [66] , so variation in loudness profiles was expected between participants even in the listening condition.

A second comparison of imagined and listening loudness profiles was made using DTW to assess how much of each passage participants were able to imagine. While image-listening similarity indicated similarity between imagined and listening loudness profiles in only as much of a passage as the participant tapped out correctly during the imagined tapping task, full-length imagined and listening loudness profiles were compared as an assessment of recall during the imagined loudness task see Appendix S1.

As not all participants were able to meet the inclusion criteria for both stimuli, expertise groups based on OMSI score tertiles were calculated separately for each stimulus to ensure that sample sizes would be similar between groups though not identical, since there were some ties in OMSI score.

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Sign In or Create an Account. Sign In. Advanced Search. Article Navigation. Close mobile search navigation Article Navigation. Volume XXI. Oxford Academic. Google Scholar. Cite Citation. Permissions Icon Permissions. Nomenclature Technique Instruction Another big part of playing music is technique or how you approach an instrument to produce sound quality.

This not covered in our courses. However, it is an essential part of learning to play. In most traditional teaching the music elements are typically taught bit by bit. An approach that allows you to slowly be able to grasp the elements, on a build as you go basis. Have you ever wondered how the teacher knows what to teach next. Well, they have the big picture.

It probably took them a long time to get there as well. Advantage In presenting the basic music theory elements at the workshop, we designed the information to give you a bigger picture of the component being studied. As you explore the individual elements and components you will start with a big picture or overview of the element and then exam each component that makes it up.

diaricosena.gq When I first started to learn music I was taught with the John Thompson method books. It was brutal. I learned one note and where it was on a keyboard. I had no concept of what the notes were and how they were related to each other, let alone what or how the the basic music theory elements even existed.

You would then go on to another note, then another.