scholarly journals Training & Evaluation System of Intelligent Oral Phonics Based on Speech Recognition Technology

2018 ◽  
Vol 13 (04) ◽  
pp. 45 ◽  
Author(s):  
Zhaoxia Yin
Keyword(s):  
Speech Recognition ◽  
Evaluation System ◽  
Corrective Feedback ◽  
Implementation Process ◽  
English Learning ◽  
Speech Recognition Technology ◽  
Shape Correction ◽  
Rating Method ◽  
English Literacy ◽  
Learning Software

The majority of Chinese people are still bound up in "dumb" English today. The English learning software is ubiquitous in our lives, but most of them merely fo-cus on English literacy without pronunciation evaluation and corrective feedback enabled. How to improve the oral English learning efficiency and quality has more and more become a hotspot of people’s common concern. The maturity of Speech Recognition Technology (SRT) has kicked off a new mode of oral Eng-lish learning, which allows the learning software enable pronunciation evaluation and feedback function. This paper probes into the speech signal extraction and pattern matching in SRT. For the sake of ease learning, the Android mobile phone platform is introduced for learner whereby to propose a rating method based on Adaptive Parameters (AP), create a mouth shape correction, and design intelligent English oral phonics training and evaluation system. This paper de-scribes the system implementation process in detail and gives a test demonstration for the system's availability.

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.

Voice Assistant — Application of Speech Recognition Technology in the Android System

2014 ◽  
Vol 596 ◽  
pp. 384-387
Author(s):  
Ge Liu ◽  
Hai Bing Zhang
Keyword(s):  
Speech Recognition ◽  
Service Providers ◽  
Voice Recognition ◽  
Working Process ◽  
Bottleneck Problems ◽  
Speech Recognition Technology ◽  
Android System ◽  
The Voice

This paper introduces the concept of Voice Assistant, the voice recognition service providers, several typical Voice Assistant product, and then the basic working process of the Voice Assistant is described in detail and proposed the technical bottleneck problems in the development of Voice Assistant software.

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