Daniel Pinchasow
Queens College, CUNY
Author Note
Daniel Pinchasow is a Junior at Queens College, CUNY, majoring in Psychology with a minor in the Pre-Health Services.
This experiment was supervised by the Department of Psychology of Queens College. Any questions regarding this experiment, please contact 718-997-3200 or email: qc_psychology@qc.cuny.edu.
Abstract
Pitch memory is one of the basic types of musical memory that illustrates the musicians’ ability to develop a high capacity for keeping musical information in their memories. Practice can make pitch memory become automatic and be done without conscious effort. The current study determines participants’ differences in recognizing pitch based on their gender and musical training differences. A sample size of 39 participants is used to determine whether musical training and gender influence their ability to recognize pitch. The study employed regression analysis and t-test. Results from regression analysis confirmed that musical training did not significantly impact the participant’s ability to recognize pitch. At the same time, regression analysis on gender confirmed that gender did not have a significant impact on participants’ ability to recognize pitch. Thus, it was evident that both gender and musical training does not influence pitch memory.
Keywords: Pitch, training, sample t-test, regression analysis
Introduction: Psychology Lab Report on Pitch Memory
In music, the pitch is one of the main building blocks, forming a key factor for music perception (Kristin, 2015). From a musical perspective, pitch describes the position of a sound in a musical scale. Pitch memory related to the auditory attribute of musical tones is an essential factor for the cumulative role of auditory material. For instance, pitch memory helps people recognize whether they are listening to a particular song for the first time (Gaab & Schlaug, 2003). From a musical perspective, pitch describes the position of a sound on a musical scale. Therefore, humans are generally good at processing auditory pitch in working memory and can distinguish pitches a few hertz apart when heard in close succession (Van Hedger, Heald, & Nusbaum, 2018).
Human beings usually distinguish between recognition and recall responses during pitch memory test (Ben-Haim, Eitan, & Chajut, 2014). Recall test involves reproducing learned material in a particular way. The current study focused on recognition response among participants. Recognition tasks are commonly used in pitch memory experiments where participants learn material and information to judge if an item was presented before or is a new one (Gaab & Schlaug, 2003). Another approach involves requiring participants to judge whether two stimuli are the same or different (Van Hedger et al., 2018).
Some researchers argue that pitch memory abilities are influenced by musical expertise and training (Ben-Haim et al., 2014). Highly trained musicians have superior pitch memory abilities than non-musicians who lack musical education (Kristin, 2015). On the other hand, a population with music disorder is usually characterized by impaired pitch perception (Gaab & Schlaug, 2003). However, the only similarity between trained and untrained individuals is that they can find it challenging to remember or recall a single isolated pitch without a reference tone.
The notion of pitch relationship and patterns underlying music processing is central to understanding music theory. In music theory, concepts like pitch intervals, musical keys, and pitch-class sets address pitch relationships (Ben-Haim et al., 2014). Accordingly, two melodies are treated as identical if they have an equivalent relationship in their constituent pitches, even if they do not have common pitches (Ben-Haim et al., 2014). The current experiment investigates the differences in pitch memory, particularly recognition among trained and untrained individuals. The experiment’s purpose is to determine the participants’ ability to remember the target tone based on gender and music training differences.
Method
Participants
There were 39 randomly selected participants. Each participant volunteered to be a part of this experiment. The ages ranged from 19-53 years old, with a mean of 23.08. Of the 39 participants, 22 were female, and 17 were male; 25 participants had no musical training, 10 had some form of instrumental training, 2 had some form of vocal training, and the last 2 participants had both instrumental and vocal training. Prior to giving the experiment, none of the participants had any knowledge of what the study was.
Materials
A computer with a keyboard, working speakers, and access to Wi-Fi was required to be a part of the experiment on the APA online psychology laboratory website.
Experimental Design
Experimental design entails the approach used to allocate participants to different groups in an experiment. For any experimental research, there is a need to determine how to distribute samples to various experimental groups. The current investigation used repeated measures experimental design that allowed the participants to participate in each condition of the independent variables, gender, and musical training. Thus, each of the conditions of the experiment included the same group of participants. Repeated measures design was preferred because it had more statistical power to control factors that cause variability between subjects like gender and musical training. Therefore, for this experiment, each participant underwent the test for pitch memory and judged whether the sounds played in the sequence were the same or different. The experiment also offered 76 trials to each participant opportunity to participate in each independent variable’s conditions.
Procedure
Participants logged onto the APA online psychology laboratory website and clicked on “Memory Pitch”. When participants had access to the experiment, the website asked the participants to “please select from the list that describes your musical training”. If a participant clicked on any form of musical training, the website asked the participants to list the number of years of training they had. If a participant clicked on “none”, the website continued to the next set of instructions. Participants clicked “START”, and the website provided three sample sounds. The first sound played was a deep pitch beep sound, then a medium beep pitch sound, and lastly, a high pitch beep sound was played. After the sounds were played, the participants clicked on “continue.” The website provided two options: “Would you like to hear a sample sequence?” or “Continue.” There were two sample sequences provided. Both sample sequences consisted of six random sounds; first random sound, pause for two seconds, five consecutive random sounds, pause for two seconds, last random sound played. Next, the website provided the goal for the experiment: “Your job is to judge whether the 1st sound played in the sound sequence were the same or different to the last sound played”. The website also provided another set of two sample sequences, which consisted of: the first and last sounds sounding the same or the first and last sounds sounding different. After the set of instructions were given, the participants began the first of 76 trials. Once the experiment started, the first trial sound sequence was automatically played. After the sound sequence was played, the website asked: “Were the first and last sounds in the previous sequence the same or different?”. The participants chose either “same” or “different” for all 76 trials. When an answer was selected, the website automatically marked the answer as correct or incorrect. When all 76 trials were completed, the experiment came to an end. Each participant’s results were calculated by the website and submitted to the instructor in charge of the experiment.
Results
The study confirmed a statistically significant difference between the group means of same pitch correct score and different pitch correct score. Furthermore, there was little evidence to argue that gender and music training impacted pitch memory. Table 1 below shows that the percentage correct score for recognizing the same pitch had a mean greater than that for the mean percentage score for recognizing different pitch. Additionally, the scores for correctly recognizing the same pitch reported a lower variance than recognizing a different pitch.
From table 1 above displaying results for the t-test, in the variance section, it is evident that the two variances are quite different hence the assumption that the variances are not equal. The two-tailed results also show that the calculated p-value is less than the standard significance level of 0.05. Thus, the decision is to reject the null hypothesis and support the hypothesis that the two population means are different.
Results in appendix 1 show that the percentage of correct same pitch scores had a small value of R square, indicating that a small percentage of the results from music training explained the results’ pattern of results when reporting on the correct same. In the second table, the significance F score is at 0.094, which is greater than 0.05, indicating that the variable music training was not significant in explaining the correct same pitch scores.
The results from coefficients table 2 show that the independent variable music training scored a p-value of 0.09419>0.05. The large coefficient p-value suggests that the correct same pitch score changes are not associated with music training changes. Thus, the predictor variable is not a meaningful addition to the model since its values are not related to changes in the response variable. On the same note, the coefficients results from the same table shows that music training had a small coefficient score, meaning that there is a minor change in the correct same pitch score when there is a unit change in music training as illustrated in the equation below:
Results in appendix 2 show that the percentage of the correct different pitch had a small R square value such that only 18.5% of the variations in the correct different pitch scores were explained by music training. The ANOVA table also indicates that the regression analysis had a significance of 0.00627, which is less than 0.05. The significance level implies that the results were significant and that the variable music was influential in explaining the correct different pitch scores.
Table 3 above shows the coefficient results for correct different pitch scores. The table shows that the p-value for the coefficient is at 0.0063, which is smaller than the 0.05 significance level. The results indicate that the changes reported in the correct different pitch scores are associated with music training time changes. Thus, the predictor variable is a meaningful addition to the model since changes in its values are related to changes in the response variable. Additionally, the results in appendix 2 shows that music training scored a coefficient value of 3.189, indicating that a unit change in music training will be tripled when reflecting its impact on changes in the correct different pitch score as illustrated in the equation below:
Finally, Appendix 3 displays for regression analysis on gender shows that the variable scored a very small R square implying that the variations in gender explain only 0.17% of the variations in pitch memory. Furthermore, the ANOVA table also confirms that the results are not significant since it scored a p-value of 0.805, which is greater than 0.05, indicating that the variable gender is not significant in explaining pitch memory changes. The same conclusion can be found from the coefficients table 4 that shows a p-value of 0.805.
Discussion
Recognition tasks have been introduced as the main approaches used in pitch memory test experiments. Research has also shown that training influences pitch memory abilities though training does not give an individual advantage over others when recognizing a single isolated pitch without a reference tone. The current research sought to determine how factors like training influence pitch memory among trained and untrained individuals. A participant’s ability to remember a target tone was tested among trained and trained individuals to assess the relationship between music training and pitch perception. The experiment also focused on the participant’s ability to recognize the same and different pitch correctly.
The t-test results confirmed a statistically significant difference between the means for scores on recognizing the same pitch correctly and recognizing different pitches correctly. The findings had a significant implication for past studies indicating that an individual’s ability to recognize the same pitch differs from identifying different pitches. The results also showed that there was statistical evidence supporting the argument that people find it challenging to identify the same pitch, which can be a consequence of various auditory factors. These findings also open room for further studies into factors that promote ease of recognizing the same stimuli and not different stimuli.
Another part of the results sought to identify the relationship between music training and pitch identification outcomes. Past studies have shown that training plays a critical role in pitch memory. However, there is no satisfactory evidence to support this argument. The current study showed that music training did not significantly impact an individual’s capacity to correctly identify the same pitch. Furthermore, the results showed no statistically significant relationship between music training and correct identification of the same pitch.
In the other experiment, different results for regression analysis were reported on recognizing different pitches. For instance, there was a statistically significant relationship between music training and recognizing different pitches. However, the results showed that music education had minimal impact on recognizing different pitches correctly. The results have also confirmed that gender does not significantly impact an individual’s pitch memory. Generally, the results have shown that music training and gender do not affect pitch memory, opening up room for further studies into factors that influence pitch memory.
The current study sought to determine the underlying relationship between music training and pitch memory. The experiment focused on an individual’s ability to recognize the same and different pitches when interference was put in between the fast and last pitch. Past studies have outlined the possibility of music training affecting an individual’s pitch memory. The results have shown a minimal relationship between music training and an individual’s capacity to correctly identify a different pitch. However, no evidence suggests that music training can influence an individual’s ability to recognize the same pitch accurately. Furthermore, the current experiment has confirmed that gender does not significantly impact an individual’s pitch memory. Given these findings, there is a need for further research focused on the various factors that can influence pitch memory capacity.
Tables/Charts/Graphs
Table 1
| t-Test: Two-Sample Assuming Unequal Variances | ||
| 92.105 | 65.789 | |
| Mean | 79.50136842 | 56.16342105 |
| Variance | 186.102817 | 438.827433 |
| Observations | 38 | 38 |
| Hypothesized Mean Difference | 0 | |
| Df | 64 | |
| t Stat | 5.754911915 | |
| P(T<=t) two-tail | 2.6477E-07 | |
| t Critical two-tail | 1.997729654 | |
Table 2
Coefficients table for correct same pitch
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 78.02619263 | 2.36953 | 32.92898 | 5.17088E-29 |
| X Variable 1 | 1.323311086 | 0.770338 | 1.717832 | 0.094187011 |
Table 3
Coefficients table for correct different pitch
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 52.07620739 | 3.384938 | 15.38469 | 1.16735E-17 |
| X Variable 1 | 3.189187014 | 1.100449 | 2.898079 | 0.006276293 |
Table 4
Coefficient table for regression analysis on gender
| Coefficients | Standard Error | t Stat | P-value | |
| Intercept | 66.35951 | 7.463179 | 8.891588 | 1.02E-10 |
| X Variable 1 | 1.224214 | 4.912866 | 0.249185 | 0.804596 |
Appendix
Appendix 1
Regression analysis for percentage correct same
| Regression Statistics | |||||
| R Square | 0.073864 | ||||
| Adjusted R Square | 0.048834 |
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 1 | 520.0473 | 520.0473 | 2.950946 | 0.094187 |
| Residual | 37 | 6520.535 | 176.2307 | ||
| Total | 38 | 7040.583 |
Appendix 2
Regression analysis for percentage correct different
| Regression Statistics | |
| R Square | 0.185002 |
| Adjusted R Square | 0.162975 |
| ANOVA | |||||
| Df | SS | MS | F | Significance F | |
| Regression | 1 | 3020.501 | 3020.501 | 8.398861 | 0.006276 |
| Residual | 37 | 13306.39 | 359.6322 | ||
| Total | 38 | 16326.89 |
Appendix 3
Regression analysis results on gender and pitch memory
| Regression Statistics | ||||
| R Square | 0.001675 | |||
| Adjusted R Square | -0.02531 |
| ANOVA | |||||
| df | SS | MS | F | Significance F | |
| Regression | 1 | 14.37215 | 14.37215 | 0.062093 | 0.804596 |
| Residual | 37 | 8564.037 | 231.4605 | ||
| Total | 38 | 8578.409 |
By Daniel Pinchas
Phone number: +1 347 5421 265
