An Evaluation Method of English Teaching Ability Based on Deep Learning

Song, Chunyan

doi:10.1155/2022/8339137

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…. Generation experiments chose using the NetworkX [21][22][23][24][25][26] network package. NetworkX is a network modelling tool developed based on the python platform.…”

Section: Resultsmentioning

confidence: 99%

Building Interior Layout Design Based on Building Information Model and Deep Learning Technology: Taking the Interior Renewal Design of the Fifth Floor of the Procuratorate of Dong Xi Hu District as an Example

Pan

Zheng

Hutter

et al. 2022

Computational Intelligence and Neuroscience

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With the development of the Internet era and the information age, electronic information technology has profoundly affected human life and work, and the architectural design industry is no exception. Architectural design has a complex design period, and the arbitrary division of labour reflects the particularity of its working process. At present, the integration of electronic information technology and scientific and technological software into architectural design has dramatically improved the work efficiency of designers. However, due to the enormous workload of drawing and modification of building drawings, and many professional departments involved in cooperation, the error rate of drawing design is still high, which eventually leads to a series of serious problems such as stagnation of the design process and rework of construction. However, due to the enormous workload of drawing and modification of building drawings, and many professional departments involved in cooperation, the error rate of drawing design is still high, which eventually leads to a series of serious problems such as stagnation of the design process and rework of construction. The BIM building information model system is an electronic information platform for comprehensive architectural design majors. It can integrate the design drawings of various majors in the design process, correct the design problems caused by inaccurate pictures at the first time, and reduce the errors in the design process. Through the BIM system and Python programming software, cross-platform cooperation is carried out to carry out computer deep learning and a series of extra design work. This paper puts forward the interior design method of the BIM system and shows the research work of interior design by the BIM building information platform through practical cases. By comparing with traditional design methods, the advantages of this technology in interior design are demonstrated, and a reference for future interior design informatization is provided.

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“…. Generation experiments chose using the NetworkX [21][22][23][24][25][26] network package. NetworkX is a network modelling tool developed based on the python platform.…”

Section: Resultsmentioning

confidence: 99%

Building Interior Layout Design Based on Building Information Model and Deep Learning Technology: Taking the Interior Renewal Design of the Fifth Floor of the Procuratorate of Dong Xi Hu District as an Example

Pan

Zheng

Hutter

et al. 2022

Computational Intelligence and Neuroscience

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“…Sensor networks principal job is to acquire data [1,2]. Although fact that sensor technology is constantly evolving further effective at collecting information from physical world, SNs are classically small, low-cost devices with restricted computing, storing, communication abilities to handle scenarios connecting widespread usage [3,4].English is widely spoken, vital language around the world. Accordingly, it is widely spoken throughout country.…”

Section: Introductionmentioning

confidence: 99%

English Speaking Assessment Algorithm Based on Deep Learning

Xiaoli Hu

2024

jes

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English as a Foreign Language (EFL) students perform when speaking in public. An increasingly globalized world, effective public speaking is critical, but EFL students struggle to perform it, despite importance of qualities such as eye contact, speech pauses, there is presently no objective examination of such elements. A summative assessment has historically been the predominant form of evaluation in college English speaking assessments. Exam-centric teaching has considerable negative effect on foreign language training. In this research work, English Speaking Assessment Algorithm Based on Deep Learning (ESA-NEGCN-NBOA) is proposed. Initially, input video data are gathered from the multiple video dataset (MVD).The input video data is then pre-processed using Deep Attentional Guided Image Filtering (DAGIF) to remove presence of signal-dependent noise and improve lack of pixels from the regions and enhanced the video data. The data that has been pre-processed is utilized to Feature extraction using New General Double Integral Transform (NGDIT), which extract the significant attributes such as mel-frequency cepstral coefficients, energy, speech rate and pitch. Then NEGCN is proposed to improve students spoken English performance by assessmenting the English speakers. In general, NEGCN doesn’t express some adaption of optimization approaches for determining optimal parameters to promise exact improvement of assessment. Therefore, NBOA is proposed to enhance weight parameter of NEGCN for English speaking assessments, which precisely assess the English speaking. Performance measures such as accuracy, assessment error, evaluation time, pretest and posttest are examined when the proposed ESA-NEGCN-NBOA method is put into practice. The proposed ESA-NEGCN-NBOA method attains21.36%, 23.42% and 19.29% higher accuracy, 23.36%, 18.42% and 28.27% lower evaluation error, 20.36%, 27.42%, 28.17% lesser evaluation time analysed with existing techniques, likes innovative strategy towards oral English assessment utilizing machine learning, data mining, blockchain methods(IST-OEA-ML), machine learning assessment system for spoken English depend on linear predictive coding (AS-SE-LPC-ML), multimodal transfer learning for oral presentation assessment (MM-TL-OPA) respectively.

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“…Tis article has been retracted by Hindawi, as publisher, following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of systematic manipulation of the publication and peer-review process.…”

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confidence: 99%

Retracted: An Evaluation Method of English Teaching Ability Based on Deep Learning

2023

Security and Communication Networks

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An Evaluation Method of English Teaching Ability Based on Deep Learning

Cited by 6 publications

References 17 publications

Building Interior Layout Design Based on Building Information Model and Deep Learning Technology: Taking the Interior Renewal Design of the Fifth Floor of the Procuratorate of Dong Xi Hu District as an Example

Building Interior Layout Design Based on Building Information Model and Deep Learning Technology: Taking the Interior Renewal Design of the Fifth Floor of the Procuratorate of Dong Xi Hu District as an Example

English Speaking Assessment Algorithm Based on Deep Learning

Retracted: An Evaluation Method of English Teaching Ability Based on Deep Learning

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