scholarly journals SISTEM PAKAR DIAGNOSA KERUSAKAN MOTOR KAWASAKI KLX150 MENGGUNAKAN METODE CASE-BASED REASONING DENGAN ALGORITMA 3W-JACCARD

2021 ◽  
Vol 8 (01) ◽  
pp. 1-8
Author(s):  
Akhmad Rezki Purnajaya ◽  
Fatma Indriani ◽  
Mohammad Reza Faisal
Keyword(s):  
Speech Recognition ◽  
Statistical Inference ◽  
Training Data ◽  
Case Based Reasoning ◽  
Android Application ◽  
Regional Language ◽  
Black Box Testing ◽  
Local Residents ◽  
Translation Accuracy ◽  
The Voice

Banjar language used in conversation and daily life around the area. So foreigners who come to the regions of South Kalimantan will have difficulty in communicating. Besides, most local residents in the backwoods of South Kalimantan can not use Indonesian language properly, they would be more convenient to use regional language to interact. For that reason we need an Android application can help users to find the translation of a word or phrase whenever and wherever. With the help of Google Voice Search, this application can also listen to the voice of the user to be converted into text and insert into the input translation. Speech recognition of Banjar language required a literacy training data by using the method of statistical inference to make results appropriated. Testing using method of Black Box Testing to measure the percentage of suitability of the results of translation, speech recognition for Indonesian language and speech recognition Banjar language using method of Statistical inference. So the results of translation accuracy 100% and accuracy of speech recognition Indonesian language and Banjar language by 97.85% and 82.74%.

scholarly journals Phonetic Variation Modeling and a Language Model Adaptation for Korean English Code-Switching Speech Recognition

2021 ◽  
Vol 11 (6) ◽  
pp. 2866
Author(s):  
Damheo Lee ◽  
Donghyun Kim ◽  
Seung Yun ◽  
Sanghun Kim
Keyword(s):  
Speech Recognition ◽  
Language Model ◽  
Reduction Rate ◽  
Code Switching ◽  
Training Data ◽  
Target Domain ◽  
Phonetic Variation ◽  
Language Model Adaptation ◽  
Imbalanced Training Data ◽  
Lm Adaptation

In this paper, we propose a new method for code-switching (CS) automatic speech recognition (ASR) in Korean. First, the phonetic variations in English pronunciation spoken by Korean speakers should be considered. Thus, we tried to find a unified pronunciation model based on phonetic knowledge and deep learning. Second, we extracted the CS sentences semantically similar to the target domain and then applied the language model (LM) adaptation to solve the biased modeling toward Korean due to the imbalanced training data. In this experiment, training data were AI Hub (1033 h) in Korean and Librispeech (960 h) in English. As a result, when compared to the baseline, the proposed method improved the error reduction rate (ERR) by up to 11.6% with phonetic variant modeling and by 17.3% when semantically similar sentences were applied to the LM adaptation. If we considered only English words, the word correction rate improved up to 24.2% compared to that of the baseline. The proposed method seems to be very effective in CS speech recognition.

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.

Application of the C4.5 Algorithm to Predict the Types of Disease in Pigs Based on Android

2021 ◽  
Vol 10 (1) ◽  
pp. 105
Author(s):  
I Gusti Ayu Purnami Indryaswari ◽  
Ida Bagus Made Mahendra
Keyword(s):  
Programming Language ◽  
Test Data ◽  
Training Data ◽  
Data Sets ◽  
Android Application ◽  
C4.5 Algorithm ◽  
Sqlite Database

Many Indonesian people, especially in Bali, make pigs as livestock. Pig livestock are susceptible to various types of diseases and there have been many cases of pig deaths due to diseases that cause losses to breeders. Therefore, the author wants to create an Android-based application that can predict the type of disease in pigs by applying the C4.5 Algorithm. The C4.5 algorithm is an algorithm for classifying data in order to obtain a rule that is used to predict something. In this study, 50 training data sets were used with 8 types of diseases in pigs and 31 symptoms of disease. which is then inputted into the system so that the data is processed so that the system in the form of an Android application can predict the type of disease in pigs. In the testing process, it was carried out by testing 15 test data sets and producing an accuracy value that is 86.7%. In testing the application features built using the Kotlin programming language and the SQLite database, it has been running as expected.

scholarly journals Realization of speech in design intent of geometric modelling

2017 ◽  
Vol 7 (1.3) ◽  
pp. 121
Author(s):  
Sreeja B P ◽  
Amrutha K G ◽  
Jeni Benedicta J ◽  
Kalaiselvi V ◽  
Ranjani R
Keyword(s):  
Speech Recognition ◽  
Geometric Modeling ◽  
Geometric Modelling ◽  
Design Intent ◽  
Voice Input ◽  
Interactive Mode ◽  
Modeling Software ◽  
Speech Recognition Engine ◽  
The Voice ◽  
Geometric Designs

The conventional interactive mode is especially used for geometric modeling software. This paper describes, a voice-assisted geometric modeling mechanism to improve the performance of modeling, speech recognition technology is used to design this model. This model states that after receiving the voice command, the system uses the speech recognition engine to identify the voice commands, then the voice commands identified are parsed and processed to generate the geometric design based on the users voice input dimensions, The outcome of the system is capable of generating the geometric designs to the user via speech recognition. This work also focuses on receiving the feedback from the users and customized the model based on the feedback.

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.

scholarly journals Android Based Voice Activated Wheel Chair for Disabled

2020 ◽  
Vol 9 (3) ◽  
pp. 3508-3509
Keyword(s):  
Speech Recognition ◽  
Smart Phone ◽  
Dc Motor ◽  
Older Individuals ◽  
Recognition Model ◽  
Human Voice ◽  
Dc Motors ◽  
Wheel Chair ◽  
The Voice

The aim of the project is to develop a wheel chair which can be controlled by voice of the person. It is based on the speech recognition model. The project is focused on controlling the wheel chair by human voice. The system is intended to control a wheel seat by utilizing the voice of individual. The structure of this framework will be particularly valuable to the crippled individual and furthermore to the older individuals. It is a booming technology which interfaces human with machine. Smart phone device is the interface. This will allow the challenging people to move freely without the assistant of others. They will get a moral support to live independently .The hardware used are Arduino kit, Microcontroller, Wheelchair and DC motors. DC motor helps for the movement of wheel chair. Ultra Sonic Sensor senses the obstacles between wheelchair and its way.

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