Evidence map›Paper›PMID 35855805›Full record

ArticleComputational intelligence and neuroscience2022

Optimization of Vocal Singing Training Methods Using Intelligent Big Data Technology.

Yong Lin, Kang Mao

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Yong LinConservatory of Music, Jeonbuk National University, Jeonju 561756, Republic of Korea.
Kang MaoConservatory of Music, Huaiyin Normal University, Jiangsu 223300, China.ORCID https://orcid.org/0000-0002-0016-5142

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of art education and information technology has led to the importance of computer technology and multimedia technology in the development of students' independent inquiry and research skills. In the context of "Internet+," new modes of teaching phonics have emerged, reconfiguring the spatial and temporal relationship of phonics education. The use of Internet resources is not only a simple collection and sharing of educational resources, but also a new way of teaching voice, which has the magic charm of becoming one of the resources for the majority of voice enthusiasts. However, in practice, there are very few assistive software suitable for music classroom teaching. It is important to research and implement teaching aids suitable for music classroom teaching. Based on intelligent big data technology to optimize the phonetic training methods, the teaching methods are more specific, scientific, and diverse, and improve the self-learning ability and learning interest of Chinese phonetic learners. The experimental results show that the weight of the phonetic teaching optimization process is 0.154 higher than the weight before processing, which is expressed as the value of the control reliability fuzzy quantifier in this test. In other words, the reliability is "absolutely reliable." Therefore, this study is expected to promote the modernization and scientific process of Chinese vocal education and propose a new way of thinking for Chinese vocal education.

Indexed as

SingingBig DataHumansLearningReproducibility of ResultsTeachingTechnology

Identifiers

PMID35855805
PMCPMC9288341

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.