A Design of a Speech Conversion System from PuTongHua to Cantonese Based on iFLY MSP 2.0

2013 ◽  
Vol 373-375 ◽  
pp. 504-508
Author(s):  
Rong Gui Ma ◽  
Fang Zhou Liu
Keyword(s):  
Speech Recognition ◽  
Learning System ◽  
Computer Assisted ◽  
Text To Speech ◽  
Computer Assisted Learning ◽  
Key Technology ◽  
Conversion System ◽  
Recognition Function ◽  
Text Information ◽  
The Voice

The paper analyzes the working theory of a Speech Conversion System from PuTongHua to Cantonese based on iFLY MSP 2.0. In the system, QISR interface is chosen to complete speech recognition function which is the key technology to convert the voice information into the corresponding text information. Moreover, the QTTS interface is chosen to complete the text to speech function which is the key technology to transform the text which is the result of the speech recognition into the spoken information in Cantonese and then output. Finally, the computer assisted learning system is designed successfully in the environment of Visual C++ 6.0.

Research and Design of Electronic Speech Reader Based on Text-to-Speech Technology

2012 ◽  
Vol 433-440 ◽  
pp. 4883-4887
Author(s):  
Hong Li Yang ◽  
Yun Yang ◽  
Zhu Yue
Keyword(s):  
Computer Technology ◽  
Speech Processing ◽  
Sound Signal ◽  
Current Development ◽  
Text To Speech ◽  
Speech Technology ◽  
Key Technology ◽  
Text Information ◽  
Voice Service ◽  
Research And Design

TTS, namely text-to-speech, is a kind of technology who can convert text information into sound signal according to information Speech processing rules. TTS, as the synthetic technology of the pronunciation, is the key technology in the current development of computer technology, and one of the most forward technical in its voice service, telephone banking, and information home appliances, mobile PDA fields. TTS has its extensive applications. In this paper, TTS is applied to electronic speech reader, which changes traditional way to read e-book, and both listening to and novels and learning English. This article introduces a method about how to make use of TTS technology, and how to achieve an electronic Speech reader of programming based on Visual Studio C# 2008 environment bring API and Microsoft SAPI interface.

scholarly journals Using a Touch-Based, Computer-Assisted Learning System to Promote Literacy and Math Skills for Low-Income Preschoolers

10.28945/3550 ◽  
2016 ◽  
Vol 15 ◽  
pp. 409-429 ◽  
Author(s):  
Mark H McManis ◽  
Lilla D McManis
Keyword(s):  
Instructional Technology ◽  
Low Income ◽  
Learning System ◽  
Computer Assisted ◽  
Math Skills ◽  
Computer Assisted Learning ◽  
Learner Engagement ◽  
Low Income Children ◽  
Educational Challenges ◽  
Early Learners

The use of touch-based technologies by young children to improve academic skills has seen growth outpacing empirical evidence of its effectiveness. Due to the educational challenges low-income children face, the stakes for providing instructional technology with demonstrated efficacy are high. The current work presents an empirical study of the use of a touch-based, computer-assisted learning system by low-income preschoolers. A description of the system’s design is provided with attention to young children’s interaction with touch devices, learner engagement, and pedagogically-based delivery of academic content. Children in 18 low-income child-care preschool classrooms were assessed on literacy and math skills in the fall and again in the spring. Target children used the iStartSmart learning system throughout the academic year, while control children did not have access to the system. Compared to controls, children using the learning system made significant gains on external standardized measures of literacy and math. Children who spent more time using the system and those who reached the upper levels of skill understanding showed the strongest improvement in test scores. The findings contribute to the currently sparse literature by illuminating that for at-risk early learners, touch-based, computer-assisted instructional technology shows promise as an educational tool.

scholarly journals The Voice Enabled Personal Assistant for Pc using Python

2021 ◽  
Vol 10 (4) ◽  
pp. 162-165
Author(s):  
Geetha V. ◽  
Gomathy C K ◽  
Manasa Sri Vardhan Kottamasu ◽  
Nukala Pavan Kumar
Keyword(s):  
Speech Recognition ◽  
Text To Speech ◽  
Voice Command ◽  
Conversational Interfaces ◽  
Personal Assistant ◽  
Personal Assistants ◽  
The Voice

Personal Assistants, or conversational interfaces, or chat bots reinvent a new way for individuals to interact with computes. A Personal Virtual Assistant allows a user to simply ask questions in the same manner that they would address a human, and are even capable of doing some basic tasks like opening apps, reading out news, taking notes etc., with just a voice command. Personal Assistants like Google Assistant, Alexa, Siri works by Speech Recognition (Speech-to-text) and Text-to-Speech.

A Research on HMM based Speech Recognition in Spoken English

2021 ◽  
Vol 14 ◽  
Author(s):  
Na Wang ◽  
Xiaohong Zhang ◽  
Ashutosh Sharma
Keyword(s):  
Speech Recognition ◽  
Recognition Accuracy ◽  
Recognition System ◽  
Learning System ◽  
Computer Assisted ◽  
Speech Signals ◽  
English Learning ◽  
Speech Recognition System ◽  
Spoken English ◽  
High Recognition Accuracy

: The computer assisted speech recognition system enabling voice recognition for understanding the spoken words using sound digitization is extensively being used in the field of education, scientific research, industry, etc. This article unveils the technological perspective of automated speech recognition system in order to realize the spoken English speech recognition system based on MATLAB. A speech recognition technology has been designed and implemented in this work which can collect the speech signals of the spoken English learning system and then filter those speech signals. This paper mainly adopts the preprocessing module for the processing of the raw speech data collected utilizing the MATLAB commands. The method of feature extraction is based on HMM model, codebook generation and template training. The research results show that the recognition accuracy of 98% is achieved by the spoken English speech recognition system studied in this paper. It can be seen that the spoken English speech recognition system based on MATLAB has high recognition accuracy and fast speed. This work addresses the current research issued needed to be tackled in the speech recognition field. This approach is able to provide the technical support and interface for the spoken English learning system.

Sign in / Sign up

Export Citation Format

Share Document