Using Computer Speech Recognition Technology to Evaluate Spoken English

2020 ◽  
pp. 1-12
Author(s):  
Duan Ran ◽  
Wang Yingli ◽  
Qin Haoxin

Artificial intelligence speech recognition technology is an important direction in the field of human-computer interaction. The use of speech recognition technology to assist teachers in the correction of spoken English pronunciation in teaching has certain effects and can help students without being constrained by places, time and teachers. Based on artificial intelligence speech recognition technology, this paper improves and analyzes speech recognition algorithms, and uses effective algorithms as the system algorithms of artificial intelligence models. Meanwhile, based on phoneme-level speech error correction, after introducing the basic knowledge, construction and training of acoustic models, the basic process of speech cutting, including the front-end processing of speech and the extraction of feature parameters, is elaborated. In addition, this study designed a control experiment to verify and analyze the artificial intelligence speech recognition correction model. The research results show that the method proposed in this paper has a certain effect.


2021 ◽  
Vol 2136 (1) ◽  
pp. 012048
Author(s):  
Xuan Zhou

Abstract Speech recognition, as one of the key artificial intelligence technologies in modern development, plays an important role in any aspect. However, there are still problems in practical application, such as poor anti-interference and low degree of perfection. Therefore, this paper aims at the content of existing computer speech recognition technology, grasps fuzzy mathematical algorithm, and analyzes how to use this algorithm to better study computer speech recognition.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Qianyu Cao ◽  
Hanmei Hao

Oral English, as a language tool, is not only an important part of English learning but also an essential part. For nonnative English learners, effective and meaningful voice feedback is very important. At present, most of the traditional recognition and error correction systems for oral English training are still in the theoretical stage. At the same time, the corresponding high-end experimental prototype also has the disadvantages of large and complex system. In the speech recognition technology, the traditional speech recognition technology is not perfect in recognition ability and recognition accuracy, and it relies too much on the recognition of speech content, which is easily affected by the noise environment. Based on this, this paper will develop and design a spoken English assistant pronunciation training system based on Android smartphone platform. Based on the in-depth study and analysis of spoken English speech correction algorithm and speech feedback mechanism, this paper proposes a lip motion judgment algorithm based on ultrasonic detection, which is used to assist the traditional speech recognition algorithm in double feedback judgment. In the feedback mechanism of intelligent speech training, a double benchmark scoring mechanism is introduced to comprehensively evaluate the speech of the speech trainer and correct the speaker’s speech in time. The experimental results show that the speech accuracy of the system reaches 85%, which improves the level of oral English trainers to a certain extent.


Author(s):  
Aliv Faizal M ◽  
Akhmad Alimudin

English pronunciation has long been taught through the delivery of phonetic symbols to study the sound of each phoneme in English. In Multimedia Broadcasting study program at Surabaya State Electronics Polytechnic, pronunciation has long been delivered to the students through guidebooks in the form of phonetic symbols that teach basic sound pronunciation in English. English teachers practice the sound of each phoneme directly to thestudents. After going through various observations based on the track record of student achievement of this pronunciation material, I as a teacher as well as researcher found that my student achievement was less than the desired target. This was due to the limited source of English pronunciation learning where students only learned face-to-face in the classroom. Through the use of English learning media of pronunciation interactively using speech recognition technology, it was expected that Multimedia Broadcasting course students in Surabaya State Electronics Polytechnic could improve their English pronunciation ability. After students complete the English pronunciation training sequence using pronunciation application using speech recognition technology, the data from the interview stated that the students felt more confident and improved their pronunciation ability and also felt the increased motivation to learn English pronunciation using English pronunciation learning app using speech recognition technology.Keywords: English pronunciation, teaching, multimedia, speech recognition technology, and pronunciation app.


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