English Pronunciation Error Automatic Correction System Based on DTW Algorithm

2020 ◽  
Vol 29 (5) ◽  
Author(s):  
Dou Ru
Keyword(s):  
Automatic Correction ◽  
English Pronunciation ◽  
Correction System

scholarly journals Automatic Correction of Arabic Dyslexic Text

Computers ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 19 ◽  
Author(s):  
Maha Alamri ◽  
William Teahan
Keyword(s):  
Word Processing ◽  
Language Model ◽  
Text Compression ◽  
Arabic Text ◽  
Automatic Correction ◽  
Compression Scheme ◽  
Candidate List ◽  
Arabic Word ◽  
Processing Software ◽  
Correction System

This paper proposes an automatic correction system that detects and corrects dyslexic errors in Arabic text. The system uses a language model based on the Prediction by Partial Matching (PPM) text compression scheme that generates possible alternatives for each misspelled word. Furthermore, the generated candidate list is based on edit operations (insertion, deletion, substitution and transposition), and the correct alternative for each misspelled word is chosen on the basis of the compression codelength of the trigram. The system is compared with widely-used Arabic word processing software and the Farasa tool. The system provided good results compared with the other tools, with a recall of 43%, precision 89%, F1 58% and accuracy 81%.

Development of a Drift-Correction Procedure for a Photoelectric Spectrometer

1978 ◽  
Vol 32 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Gilbert B. Chapman ◽  
William A. Gordon
Keyword(s):  
Optical Path ◽  
Automatic Correction ◽  
Sample Analysis ◽  
Electronic Components ◽  
Drift Correction ◽  
Direct Reading ◽  
Coefficients Of Variation ◽  
Lamp Current ◽  
Analytical Calibration ◽  
Correction System

This procedure provides automatic correction for drifts in the radiometric sensitivity of each detector channel in a direct-reading emission spectrometer. Such drifts are customarily controlled by the regular analyses of standards, which provide corrections for changes in the excitational, optical, and electronic components of the instrument. This standardization procedure, however, corrects for the optical and electronic drifts, thus minimizing the time, effort, and cost of regularly processing standards. This method of radiometric drift correction uses a 1000-W tungsten-halogen reference lamp to illuminate each detector through the same optical path as that traversed during sample analysis. The responses of the detector channels to this reference light are regularly compared with channel responses to the same light intensity at the time of analytical calibration in order to determine and correct for drift. The coefficients of variation of these drift corrections average less than 1%. Except for placing the lamp in position, the procedure is fully automated and compensates for changes in spectral intensity due to variations in lamp current. A discussion of the implementation of this drift-correction system is included.

System of Automatic Correction and Measurement for Hypoid Gears

2011 ◽  
Vol 464 ◽  
pp. 155-158 ◽  
Author(s):  
Tian Xing Li ◽  
Xiao Zhong Deng ◽  
Zhen Shan Gao ◽  
Ju Bo Li
Keyword(s):  
Closed Loop ◽  
Tooth Surface ◽  
Milling Machine ◽  
Automatic Correction ◽  
Hypoid Gears ◽  
Surface Deviation ◽  
Deviation Measurement ◽  
The Stability ◽  
Surface Precision ◽  
Correction System

The system of automatic correction and deviation measurement of hypoid gears is the basic platform for the digital closed-loop manufacturing technology. Based on the gear measuring center and the numerical controlled gear milling machine, a measurement and correction system is developed by the application of Visual C++ and Fortran. The architecture and the implement of the main modules are elaborated. Experiments and applications indicate that the tooth surface deviation can be effectively reduced by the system of automatic correction and measurement, and the stability of tooth surface precision and manufacturing quality is improved. It would provide the foundation for the digitalization of manufacture and quality control of hypoid gears.

scholarly journals Intelligent Correction System of Students’ English Pronunciation Errors Based on Speech Recognition Technology

2021 ◽  
Vol 18 ◽  
pp. 192-198
Author(s):  
Meili Dai
Keyword(s):  
Speech Recognition ◽  
Correction Function ◽  
Practical Application ◽  
Speech Recognition Technology ◽  
English Pronunciation ◽  
Calculation Results ◽  
Execution Environment ◽  
Voice Data ◽  
Software Execution ◽  
Correction System

With the increasingly frequent international exchanges, English has become a common language for communication between countries. Under this research background, in order to correct students’ wrong English pronunciation, an intelligent correction system for students’ English pronunciation errors based on speech recognition technology is designed. In order to provide a relatively stable hardware correction platform for voice data information, the sensor equipment is optimized and combined with the processor and intelligent correction circuit. On this basis, the MLP (Multilayer Perceptron) error correction function is defined, with the help of the known recognition confusion calculation results, the actual input speech error is processed by gain mismatch, and the software execution environment of the system is built. Combined with the related hardware structure, the intelligent correction system of students’ English pronunciation error based on speech recognition technology is successfully applied, and the comparative experiment is designed the practical application value of the system is highlighted.

scholarly journals Design of an Automatic English Pronunciation Error Correction System Based on Radio Magnetic Pronunciation Recording Devices

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Zhang Shufang
Keyword(s):  
Speech Recognition ◽  
Error Correction ◽  
Block Diagram ◽  
Linear Mapping ◽  
Recording Device ◽  
Endpoint Detection ◽  
English Pronunciation ◽  
Data Driven Approach ◽  
Correction System ◽  
Pronunciation Dictionary

In this paper, a system for automatic detection and correction of mispronunciation of native Chinese learners of English by speech recognition technology is designed with the help of radiomagnetic pronunciation recording devices and computer-aided software. This paper extends the standard pronunciation dictionary by predicting the phoneme confusion rules in the language learner’s pronunciation that may lead to mispronunciation and generates an extended pronunciation dictionary containing the standard pronunciation of each word and the possible mispronunciation variations, and automatic speech recognition uses the extended pronunciation dictionary to detect and diagnose the learner’s mispronunciation of phonemes and provides real-time feedback. It is generated by systematic crosslinguistic phonological comparative analysis of the differences in phoneme pronunciation with each other, and a data-driven approach is used to do automatic phoneme recognition of learner speech and analyze the mapping relationship between the resulting mispronunciation and the corresponding standard pronunciation to automatically generate additional phoneme confusion rules. In this paper, we investigate various aspects of several issues related to the automatic correction of English pronunciation errors based on radiomagnetic pronunciation recording devices; design the general block diagram of the system, etc.; and discuss some key techniques and issues, including endpoint detection, feature extraction, and the system’s study of pronunciation standard algorithms, analyzing their respective characteristics. Finally, we design and implement a model of an automatic English pronunciation error correction system based on a radiomagnetic pronunciation recording device. Based on the characteristics of English pronunciation, the correction algorithm implemented in this system uses the similarity and pronunciation duration ratings based on the log posterior probability, which combines the scores of both, and standardizes this system scoring through linear mapping. This system can achieve the purpose of automatic recognition of English mispronunciation correction and, at the same time, improve the user’s spoken English pronunciation to a certain extent.

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