Evidence map›Paper›PMID 35800943›Full record

ArticleFrontiers in psychology2022

National Ballad Creation Education Under Artificial Intelligence and Big Data.

Xia Liu, Xiao Han, Xiao Lin, Jong Hoon Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

Xia LiuArt College, Southwest Minzu University, Chengdu, China.
Xiao HanDepartment of Digital Image, Sang Myung University, Seoul, South Korea.
Xiao LinDepartment of Digital Image, Sang Myung University, Seoul, South Korea.
Jong Hoon YangDepartment of Digital Image, Sang Myung University, Seoul, South Korea.
Sangmyung University · KRJilin College of the Arts · CNSouthwest Minzu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The efficiency of manual ballad creation is low, and the status quo of music creation education still needs to be improved. Therefore, how to upgrade the creative level of students is studied to improve the creative ability of China's unique ballad culture. The concept of music theory in the process of music creation is explained, and the application of big data in the NetEase cloud music platform is excavated. Besides, the optical music organization (OMR) method based on artificial intelligence (AI) is proposed using a learning method of style imitation. This method is applied to students' ballad creation education and tested in the school creation curriculum. It is found that the novelty of the ballads created by the system is slightly better than the existing ballads by comparing the ballads created by the machine with those used as imitation templates. In addition, the students' learning interests and creative achievement are compared through the comparative experiment. The results show that students' interest in learning has been significantly improved, and their creative performance in oral language has also been enhanced compared with the control class. As a result, this system is considered to be able to be applied in students' ballad creation courses and provide some basis for AI creation in related fields.

Indexed as

artificial intelligenceballad creationbig datalearning interestteaching work

Identifiers

PMID35800943
PMCPMC9253618
OpenAlexW4283215164

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.