MPEG Video Evaluation Method with Time-Domain Weighting

Deqiang, 程德强 Cheng; Chao, 许超 Xu; Yan, Li; Dalei, 游大磊 You; Gang, 陈刚 Chen

doi:10.3788/lop55.081011

Cited by 2 publications

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“…But it's not about the quality of pronunciation that learners use, instead, the multi-dimensional assessment features at segmental and suprasegmental levels are integrated to simulate human experts' assessment of learners' overall pronunciation level. Among them, Goodness of Pronunciation (GOP) algorithm and its improved algorithm are widely used as evaluation features in different scenarios [7] . Cucchiarini et al [8] used Hidden Markov Model (HMM) based speech recognition device to extract a series of temporal indicators, such as speaking speed, pronunciation speed, average length of speech ow, ratio of pronunciation time, number of pauses and total duration of pause.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: An English pronunciation and intonation evaluation method based on the DTW algorithm

Duan

2023

Soft Comput

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In order to solve the problems of single feature dimension and low accuracy in traditional oral English evaluation, this study has used the support vector regression algorithm to achieve the effective integration of different dimension evaluation features. The study comprehensively evaluate the overall reading and pronunciation quality of students. This paper designs an evaluation model of spoken English pronunciation quality based on a dynamic time warping algorithm and introduces the evaluation algorithms of pronunciation standard, uency, and intonation, respectively. A support vector regression algorithm is used to realize the effective fusion of different dimension evaluation features. In addition, the correlation between machine rating and manual rating was used as an evaluation index to evaluate students' oral pronunciation quality from different dimensions. The model shows superior performance in the pronunciation of both monosyllabic and polysyllabic words, which is bene cial to improving students' oral English learning effect.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: An English pronunciation and intonation evaluation method based on the DTW algorithm

Duan

2023

Soft Comput

View full text Add to dashboard Cite

show abstract

An English pronunciation and intonation evaluation method based on the DTW algorithm

Duan

2023

Preprint

View full text Add to dashboard Cite

In order to solve the problems of single feature dimension and low accuracy in traditional oral English evaluation, this study has used the support vector regression algorithm to achieve the effective integration of different dimension evaluation features. The study comprehensively evaluate the overall reading and pronunciation quality of students. This paper designs an evaluation model of spoken English pronunciation quality based on a dynamic time warping algorithm and introduces the evaluation algorithms of pronunciation standard, fluency, and intonation, respectively. A support vector regression algorithm is used to realize the effective fusion of different dimension evaluation features. In addition, the correlation between machine rating and manual rating was used as an evaluation index to evaluate students' oral pronunciation quality from different dimensions. The model shows superior performance in the pronunciation of both monosyllabic and polysyllabic words, which is beneficial to improving students' oral English learning effect.

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MPEG Video Evaluation Method with Time-Domain Weighting

Cited by 2 publications

References 0 publications

RETRACTED ARTICLE: An English pronunciation and intonation evaluation method based on the DTW algorithm

RETRACTED ARTICLE: An English pronunciation and intonation evaluation method based on the DTW algorithm

An English pronunciation and intonation evaluation method based on the DTW algorithm

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