Improving English Pronunciation Via Automatic Speech Recognition Technology

2017 ◽  
Author(s):  
Meihui Li ◽  
Meiting Han ◽  
Zejia Chen ◽  
Yiling Mo ◽  
Xiujuan Chen ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Speech Recognition Technology ◽  
English Pronunciation

Improving English pronunciation via automatic speech recognition technology

2019 ◽  
Vol 25 (2) ◽  
pp. 126
Author(s):  
Minjia Liu ◽  
Xiujuan Chen ◽  
Yiling Mo ◽  
Zejia Chen ◽  
Xiaobin Liu ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Speech Recognition Technology ◽  
English Pronunciation

Improving English pronunciation via automatic speech recognition technology

2019 ◽  
Vol 25 (2) ◽  
pp. 126 ◽  
Author(s):  
Xiaobin Liu ◽  
Manfei Xu ◽  
Meihui Li ◽  
Meiting Han ◽  
Zejia Chen ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Speech Recognition Technology ◽  
English Pronunciation

PENERAPAN TEKNOLOGY SPEECH RECOGNITION UNTUK LATIHAN PRONUNCIATION BAHASA INGGRIS MELALUI METODE DICTATION DI PROGRAM STUDI MULTIMEDIA BROADCASTING POLITEKNIK ELEKTRONIKA NEGERI SURABAYA

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Aliv Faizal M ◽  
Akhmad Alimudin
Keyword(s):  
Student Achievement ◽  
Speech Recognition ◽  
Training Sequence ◽  
English Learning ◽  
Motivation To Learn ◽  
Study Program ◽  
Face To Face ◽  
Track Record ◽  
Speech Recognition Technology ◽  
English Pronunciation

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.

Perceptual Properties of Current Speech Recognition Technology

2013 ◽  
Vol PP (99) ◽  
pp. 1-18 ◽  
Keyword(s):  
Feature Extraction ◽  
Speech Recognition ◽  
Auditory System ◽  
Automatic Speech Recognition ◽  
Auditory Processing ◽  
Auditory Perception ◽  
Automatic Recognition ◽  
Extraction Procedures ◽  
Human Auditory System ◽  
Speech Recognition Technology

In recent years, a number of feature extraction procedures for automatic speech recognition (ASR) systems have been based on models of human auditory processing, and one often hears arguments in favor of implementing knowledge of human auditory perception and cognition into machines for ASR. This paper takes a reverse route, and argues that the engineering techniques for automatic recognition of speech that are already in widespread use are often consistent with some well-known properties of the human auditory system.

scholarly journals The Usefulness of Automatic Speech Recognition (ASR) Eyespeak Software in Improving Iraqi EFL Students’ Pronunciation

2017 ◽  
Vol 8 (1) ◽  
pp. 221 ◽  
Author(s):  
Lina Fathi Sidig Sidgi ◽  
Ahmad Jelani Shaari
Keyword(s):  
College Students ◽  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Native Language ◽  
First Year ◽  
First Year College ◽  
Pronunciation Instruction ◽  
English Pronunciation ◽  
Efl Students ◽  
First Year College Students

The present study focuses on determining whether automatic speech recognition (ASR) technology is reliable for improving English pronunciation to Iraqi EFL students. Non-native learners of English are generally concerned about improving their pronunciation skills, and Iraqi students face difficulties in pronouncing English sounds that are not found in their native language (Arabic). This study is concerned with ASR and its effectiveness in overcoming this difficulty. The data were obtained from twenty participants randomly selected from first-year college students at Al-Turath University College from the Department of English in Baghdad-Iraq. The students had participated in a two month pronunciation instruction course using ASR Eyespeak software. At the end of the pronunciation instruction course using ASR Eyespeak software, the students completed a questionnaire to get their opinions about the usefulness of the ASR Eyespeak in improving their pronunciation. The findings of the study revealed that the students found ASR Eyespeak software very useful in improving their pronunciation and helping them realise their pronunciation mistakes. They also reported that learning pronunciation with ASR Eyespeak enjoyable.  

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