Study on the Influence of AI Composition Software on Students'Creative Ability in Music Education

Generative AI technology for human-assisted tools has made great strides in recent years,and studying the impact of this technology on students'compositional abilities plays an important role in promoting changes in music education.Previous studies have focused on the performance of music composition software itself in terms of composition,with less consideration given to the impact of creators'compositional ability after using assistive composition tools.Thus,this paper designs a controlled experiment to investigate the changes in students'compositional ability before and after using AI composition tools.This paper finds that students'compositional abilities in all areas of composition improved to varying degrees after using AI composition tools.This paper compares the differences in compositional abilities of students with and without the education of AI composition tools,which has practical implications for vigorously promoting the adoption of AI composition tools in university music education teaching.

Construction of Psychological Adjustment Function Model of Music Education Based on Emotional Tendency Analysis

In the face offierce competition in the social environment,mental health problems gradually get the attention of the public,in order to achieve accurate mental health data analysis,the construction of music education is based on emotional tendency analysis of psychological adjustment function model.Design emotional tendency analysis of music education psychological adjustment function architecture,music teaching goal as psychological adjust-ment function architecture building orientation,music teaching content as a foundation for psychological adjust-ment function architecture and music teaching process as a psychological adjustment function architecture building,music teaching evaluation as the key of building key regulating function architecture,Establish a core literacy oriented evaluation system.Different evaluation methods were used to obtain the evaluation results.Four levels of psychological adjustment function model of music education are designed,and the psychological adjust-ment function of music education is put forward,thus completing the construction of psychological adjustment function model of music education.The experimental results show that the absolute value of the data acquisition error of the designed model is minimum,which is not more than 0.2.It is less affected by a bad coefficient and has good performance.It can quickly converge to the best state in the actual prediction process and has a strong con-vergence ability.

Research on the Comparison and Integration of Chinese and Western Music Cultures

This research undertakes a nuanced examination of the intersections and distinctions between these two diverse musical traditions.Employing a meticulous comparative analysis,the study scrutinizes fundamental musical elements such as scales,modes,and compositional styles,illuminating shared threads and distinctive attributes that characterize Chinese and Western music.Against the backdrop of contemporary global dynamics,the research investigates the ongoing integration of these musical cultures.It explores the impact of globalization and technological advancements,revealing instances of cross-cultural collaboration and the emergence of hybrid musical forms.Augmenting theoretical discussions with concrete case studies,the paper offers illuminating examples of how Chinese and Western musical elements interweave,contributing to the evolving landscape of global music.This research not only advances scholarly understanding but also contributes practical insights for musicians,educators,and enthusiasts navigating the evolving dynamics of cross-cultural musical expression.By elucidating the intricate relationship between Chinese and Western music cultures,the paper underscores the richness borne out of their interaction and the cultural synthesis that defines contemporary musical landscapes.

Detrended Fluctuation Analysis of the Human EEG during Listening to Emotional Music

A nonlinear method named detrended fluctuation analysis （DFA） was utilized to investigate the scaling behavior of the human electroencephalogram （EEG） in three emotional music conditions （fear, happiness, sadness） and a rest condition （eyes-closed）. The results showed that the EEG exhibited scaling behavior in two regions with two scaling exponents β1 and β2 which represented the complexity of higher and lower frequency activity besides α band respectively. As the emotional intensity decreased the value of β1 increased and the value of β2 decreased. The change of β1 was weakly correlated with the ＇approach-withdrawal＇ model of emotion and both of fear and sad music made certain differences compared with the eyes-closed rest condition. The study shows that music is a powerful elicitor of emotion and that using nonlinear method can potentially contribute to the investigation of emotion.

Inheritance and Innovation of Traditional Music Culture in Modern Music Composition

Traditional music culture,from perspective of axiology,is considered the essence of arts of the era which witnesses the innovation of musical culture in various historical periods and drives the development of modern music,in which creative thoughts and ideas cherish the factor and perfection making a new request to aesthetics of its composition.Therefore,blending traditional music culture with modern music composition will generate new characteristics of classic elegance,artistic beauty and epoch aesthetics,bringing a new trend of the modern music composition into being and propelling actively to form creative thoughts and innovative ideas by utilizing inheritance and innovation of traditional music as carriers.

Mixed Music Analysis with Extended Specmurt

This paper introduces a mixed music analysis method using extended specmurt analysis. Conventional specmurt can only analyze a multi-pitch music signal from a single instrument and cannot analyze a mixed music signal that has several different types of instruments being played at the same time. To analyze a mixed music signal, extended specmurt is proposed. We regard the observed spectrum extracted from the mixed music as the summation of the observed spectra corresponding to each instrument. The mixed music has as many unknown fundamental frequency distributions as the number of instruments since the observed spectrum of a single instrument can be expressed as a convolution of the common harmonic structure and the fundamental frequency distribution. The relation among the observed spectrum, the common harmonic structure and the fundamental frequency distribution is transformed into a matrix representation in order to obtain the unknown fundamental frequency distributions. The equation is called extended specmurt, and the matrix of unknown components can be obtained by using a pseudo inverse matrix. The experimental result shows the effectiveness of the proposed method.

Research on the Developmental Trend of Computer Music Composition under the Background of Popular Music and Aesthetics

In this paper, we conduct research on developmental trend of computer music composition under the background of popular music and aesthetics. In the process of the Chinese modem music history, popular music communication for the selection of music ontology, the audience for popular music transmission and delivery of the music ontology selection process fully the outline of Chinese modem society people＇ s psychology and value concept of the construction of the trajectory and people value consciousness and change. Under this historical background, we propose novel computer music composition paradigm that will enhance and optimize the musical creation procedures.

Research on the Modern Music Composition Development Direction under the Digital and Computer Background

In this paper, we conduct research on modem music composition development direction under the digital and computer background. We can hear the music work, at ordinary times is the musician and sound engineer through three different stages of product created by mutual cooperation. The development of computer music has impact to the music every aspect of life, including various music creation process, cause the changes of some design principles. This change may be denied the traditional, also may be denied the traditional that is on the development of traditional principles. We integrate the concepts and principles of the digital perspective to propose our methodology on issues of computer music develooment that holds vital siznificance and meaning.

Research on the Accurate Computer Music Composition Mode under the Background of Big Data

In this paper, we conduct research on the accurate computer music composition mode under the basic background of big data. From the perspective of music theory, in terms of micro notes jump within a certain range, will not cause discomfort, notes there are upward at the same time, the downward makes the whole piece will not boring. From the macroscopic, the nature of the chord with internal connection between motivation and motivation as support, at the same time, the whole range can maintain in a certain range, making sound effects is can let a person feel cheerful. Computer science first occupied is music in the music sound production and the propagation of position as it is mainly used for digital audio clips and automated synthesis. But there is a certain distance away from the traditional concept of composition. Therefore, our research proposes the innovative perspective to deal with the issues for achieving the better performance.

How to Improve Old People＇s Music-Learning Level in the Aging Society —— An analysis of old people＇s psychology in the learning of music

The world has paid more and more attention to the old people＇s life, physiology and mental health, which became a popular and hot issue that attracted the expert＇s sight. Questions of how to teach them, how to create a harmonious teaching environment, how to communicate with them about the key point and how to teach them in a more scientific way need to be considered and discussed further,

Use of music during colonoscopy:An updated meta-analysis of randomized controlled trials

BACKGROUND Music seems to be beneficial in multiple clinical areas.Colonoscopy is a stressful event for patients,especially with conscious sedation.Music during colonoscopy has been evaluated in multiple randomized controlled trials(RCTs)with varied results.Even meta-analyses on the subject over the years have yielded inconsistent conclusions.Therefore,we conducted an up-to-date meta-analysis regarding music during colonoscopy.AIM To assess the effects of music played during colonoscopy on patients’perspectives and sedation requirements.METHODS Multiple large databases were aggressively searched(November 2018).RCTs comparing music to without music during colonoscopy on adult patients were included.Pooled estimates were calculated for sedative medication doses,total procedure time,and patients’experience,willingness to repeat procedure,and pain scores using odds ratio(OR)and mean difference(MD)with random effects model.RESULTS Eleven studies(n=988)were included.Music during colonoscopy showed a statistically significant reduction in procedure times(MD:-2.3 min;95%CI:-4.13 to-0.47;P=0.01)and patients’pain(MD:-1.26;95%CI:-2.28 to-0.24;P=0.02)while improving patients’experience(MD:-1.11;95%CI:-1.7 to-0.53;P<0.01)as compared to no music.No statistically significant differences were observed between music and no music during colonoscopy for midazolam(MD:-0.4 mg;95%CI:-0.9 to 0.09;P=0.11),meperidine(MD:-3.06 mg;95%CI:-10.79 to 4.67;P=0.44),or patients’willingness to repeat the colonoscopy(OR:3.89;95%CI:0.76 to 19.97;P=0.1).CONCLUSION Music appears to improve overall patient experience while reducing procedure times and patient pain.Therefore,music,being a non-invasive intervention,should be strongly considered during colonoscopy.

Effectiveness of five elements music therapy on negative emotions of tumor patients:a systematic review and grading recommendations(GRADE)system

Background:Many original studies have shown that traditional Chinese five-element therapy(FEM-therapy)can effectively relieve anxiety,depression and quality of life.However,one published systematic review refuted this conclusion.To further clarify the efficacy of FEM therapy in relieving negative emotion among cancer patients and to assess the reliability of the evidence,this systematic review and meta-analysis was performed.Methods:We searched for randomized controlled trials(RCTs)comparing FEM-therapy versus standard care for cancer patients,six databases(CBM,PubMed,Cochrane Library,Web of Science,CNKI,and WanFang),two clinical trial registries and one gray literature database were searched from inception to October 31,2022.Two investigators independently screened literature,extracted data,and assessed risk of bias according to the Cochrane Handbook Version 6.1.0.The RevMan 5.3 software was used to perform the meta-analysis.Overall quality of evidence was rated using GRADE(Grading of Recommendations,Assessment,Development and Evaluation).Results:25 RCTs involving 1990 patients were finally included.Two of which had high risk bias,the remaining 23 were rated as unclear risk bias.Compared with other treatments,FEM-therapy combined with conventional nursing can significantly relieve anxiety(MD=-10.33,95%CI:[-13.77,-6.88],P<0.05;very low certainty)and depression(SMD=-1.10,95%CI:[-1.41,-0.79],P<0.05;very low certainty),and can significantly increase the quality of sleep(MD=-2.92,95%CI:[-4.89,-0.95],P<0.05;low certainty).Compared with acupuncture intervention,FEM-therapy combined with acupuncture can decreased the anxiety(SMD=-0.64,95%CI:[-0.98,-0.30],P<0.05;Moderate certainty)and depression(SMD=-0.68,95%CI:[-1.00,-0.32],P<0.05;Moderate certainty).Conclusion:Traditional Chinese FEM therapy combined with other treatments are effective in alleviating negative emotions among cancer patients.In order to better improve the quality of life of cancer patients and give more reliable advice,more trials of direct comparisons are needed to inform clinical decision-making with greater confidence.

Multi-style Chord Music Generation Based on Artificial Neural Network

With the continuous development of deep learning and artificial neural networks(ANNs), algorithmic composition has gradually become a hot research field. In order to solve the music-style problem in generating chord music, a multi-style chord music generation(MSCMG) network is proposed based on the previous ANN for creation. A music-style extraction module and a style extractor are added by the network on the original basis;the music-style extraction module divides the entire music content into two parts, namely the music-style information Mstyleand the music content information Mcontent. The style extractor removes the music-style information entangled in the music content information. The similarity of music generated by different models is compared in this paper. It is also evaluated whether the model can learn music composition rules from the database. Through experiments, it is found that the model proposed in this paper can generate music works in the expected style. Compared with the long short term memory(LSTM) network, the MSCMG network has a certain improvement in the performance of music styles.

一种改进的干涉仪-MUSIC联合测向算法

在无线电测向方法中,干涉仪测向算法和多重信号分类(MUSIC)测向算法较为成熟,广泛应用于众多领域,但各自都有一定的优缺点。文章结合两者优点,提出一种改进的干涉仪-MUSIC联合测向算法,该算法相比于传统的干涉仪测向法和MUSIC测向法具有更高的测向精度和运算速度。首先利用俯仰角切割划分的方法,减少了干涉仪测向法运算量,而后在干涉仪测向法误差分析的基础上,灵活选取MUSIC测向搜索范围,以此将干涉仪测向法和MUSIC测向法结合,提高测向精度和运算速度的同时,增强了算法鲁棒性和适用性。通过仿真分析,证实了所提算法的有效性。文章所提联合测向改进算法为无线电测向研究提供了技术参考。

基于实值MUSIC算法的电力谐波分析方法

现代谱估计方法逐渐被应用于电力谐波及间谐波的超分辨率检测与分析,其中的多重信号分类方法(MUSIC)算法最具代表性。然而,常规谱MUSIC算法在分析电力谐波时必须将实值信号转换为复频率信号,因而计算复杂度较高;此外,其伪频谱的峰值搜索过程也存在着类似栅栏效应,导致其频率分析精度有限。为了改善谱MUSIC算法对电力谐波的分析精度,本文基于子空间分析理论提出了针对实值周期信号的谱MUSIC频率检测方法,推导并给出了其伪谱函数的表达式。在此基础上,还利用Newton-Raphson算法对伪谱峰值进行迭代求精,进一步提高了谐波频率的估计精度。仿真结果表明:实值MUSIC伪谱更能有效区分真实谐波谱峰与噪声伪峰,同时本文方法的计算复杂度远远低于原有复值谱MUSIC算法,而频率估计精度与求根MUSIC算法接近,非常有利于电力谐波参数的准确获取。

基于噪声子空间分解MUSIC函数的谐波/间谐波检测算法

针对电力系统中存在的谐波和间谐波问题,提出了基于噪声子空间分解MUSIC(DNS-MUSIC)函数的谐波/间谐波检测方法。利用信号自相关矩阵的特征值分解理论,将信号的自相关矩阵分解为信号子空间和噪声子空间,利用2个子空间的正交性进一步分解噪声子空间,对其进行变换,构造出基于噪声子空间分解的特征多项式(DNS-MUSIC函数),求解该多项式得到信号基波和谐波频率预估计,结合消噪思想检测电力系统信号频率成分,然后利用扩展Prony法检测信号的幅值和相位。通过仿真实验与其他经典算法比较,结果证明了所提算法的可行性、高效性和稳定性。

基于MUSIC功率谱和CPNN的鸡蛋散黄无损检测方法

[目的]针对当前国内外对散黄鸡蛋较难无损检测的问题,对散黄鸡蛋的振动特性和无损检测方法进行了研究。[方法]通过对鸡蛋进行生理学解剖,据此进行ANSYS有限元分析;构建基于磁致伸缩振子扫频式振动的鸡蛋散黄检测系统,对采集的鸡蛋振动音频信号进行MUSIC(multiple signal classification)功率谱分析,再利用主成分分析法提取特征向量中的有用信息并构建基于对向传播神经网络(CPNN)的鸡蛋散黄检测模型。[结果]鸡蛋的ANSYS固液耦合有限元分析证明新鲜蛋与散黄蛋振动特性差异明显,为基于振动信息的鸡蛋散黄检测提供理论依据;基于磁致伸缩振子扫频式振动的鸡蛋散黄检测系统能有效增强鸡蛋振动信息,基于对向传播神经网络的鸡蛋散黄检测模型对300枚鸡蛋进行检测(训练集200枚,测试集100枚),结果新鲜蛋与散黄蛋的识别率分别达到98%和96%。[结论]新鲜蛋与散黄蛋振动存在差异,采用基于扫频振动式的MUSIC功率谱分析和对向传播神经网络的鸡蛋散黄检测是可行的。

单矢量水听器频域极化加权MUSIC算法

针对经典多重信号分类(MUSIC)算法估计性能受限于空间随机分布噪声的问题,提出了一种基于频域极化加权的单矢量水听器MUSIC算法。该方法提取接收信号频域极化参数,根据目标信号与噪声在极化特性上的区别,对接收信号频谱自适应地加权。将加权后的频谱信号代替原接收信号,构造极化协方差矩阵,再利用经典MUSIC算法估计目标方位。仿真研究表明,在信噪比为-15 dB且无先验知识情况下,该方法的目标方位估计误差小于5°。海试数据处理结果验证了该方法的有效性。

基于两次傅里叶变换的时域MUSIC波达方向估计

针对基于频域多重信号分类(MUSIC)的波达方向(DOA)估计方法在有效快拍数较少情况下的不稳定问题,提出了一种基于两次傅里叶变换的时域MUSIC波达方向估计方法。首先,通过傅里叶变换将各阵元接收数据转换为频域数据,并按扫描角度对各阵元数据进行相位补偿;然后,再通过傅里叶变换将补偿后的频域共轭数据转换为时域复解析数据,在时域构建相移后的协方差矩阵;最后利用特征分解求取具有正交特性的噪声子空间,获得扫描方位空间谱,实现对波达方向估计。数值仿真及实测数据处理结果均表明,相比频域MUSIC方法,在一次有效快拍条件下,所提方法可稳定获得具有正交特性的噪声子空间,实现对波达方向估计;稳定性得到了5 dB的改善,背景噪声级和旁瓣级得到了3 dB以上的改善,因此该方法可明显提高目标检测和方位估计性能。