scholarly journals Research on Correction Method of Spoken Pronunciation Accuracy of AI Virtual English Reading

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shuli Wang ◽  
Xiuchuan Shi
Keyword(s):  
Speech Synthesis ◽  
Intelligent System ◽  
Correction Method ◽  
Speech Technology ◽  
Simulation Research ◽  
Correction Model ◽  
Spoken English ◽  
English Reading ◽  
Artificial Intelligence Technology ◽  
Correction System

In order to improve the pronunciation accuracy of spoken English reading, this paper combines artificial intelligence technology to construct a correction model of the spoken pronunciation accuracy of AI virtual English reading. Moreover, this paper analyzes the process of speech synthesis with intelligent speech technology, proposes a statistical parametric speech based on hidden Markov chains, and improves the system algorithm to make it an intelligent algorithm that meets the requirements of the correction system of spoken pronunciation accuracy of AI virtual English reading. Finally, this paper combines the simulation research to analyze the English reading, spoken pronunciation, and pronunciation correction of the intelligent system. From the experimental research results, the correction system of spoken pronunciation accuracy of AI virtual English reading proposed in this paper basically meets the basic needs of this paper to build a system.

Artificial intelligence speech recognition model for correcting spoken English teaching

2020 ◽  
pp. 1-12
Author(s):  
Duan Ran ◽  
Wang Yingli ◽  
Qin Haoxin
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
Basic Knowledge ◽  
Correction Model ◽  
Spoken English ◽  
Speech Recognition Technology ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Important Direction ◽  
And Training

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.

A curvature correction turbulent model for computations of cloud cavitating flows

2016 ◽  
Vol 33 (1) ◽  
pp. 202-216 ◽  
Author(s):  
Yu Zhao ◽  
Guoyu Wang ◽  
Biao Huang
Keyword(s):  
Recirculation Zone ◽  
Correction Method ◽  
Cavitating Flows ◽  
Baseline Model ◽  
Model Calculations ◽  
Correction Model ◽  
Content Type ◽  
Curvature Correction ◽  
Streamline Curvature ◽  
Cavity Shedding

Purpose – The purpose of this paper is to assess the predictive capability of the streamline curvature correction model (CCM) and investigate the unsteady vortex behavior of the cloud cavitating flows around a hydrofoil. Design/methodology/approach – The design of the paper is based on introducing the curvature correction method to the original k-ε model. Calculations of unsteady cloud cavitating flows around a Clark-Y hydrofoil are performed using both the CCM and the baseline model. Findings – Compared with the baseline model, better agreements are observed between the predictions of the CCM model and experimental data, especially the cavity shedding process. Based on the computations, it is demonstrated that streamline curvature correction of the CCM model can effectively decrease predicted turbulence kinetic energy and eddy viscosity in cavity shedding region. This leads to the better prediction for the recirculation zone located downstream of the attached cavity, and dynamics of this recirculation zone contribute to the formation and development of the re-entrant jet. Originality/value – The authors apply streamline curvature correction to the calculations of unsteady cloud cavitating flows and discuss the interactions between the cavitation unsteadiness and vortex structures to get an insight of the correction mechanics.

An Intelligent System for Online Optimization of the Cylindrical Traverse Grinding Operation

2006 ◽  
Vol 220 (3) ◽  
pp. 355-363 ◽  
Author(s):  
B W Kruszyński ◽  
P Lajmert
Keyword(s):  
Material Removal ◽  
Intelligent System ◽  
Removal Rate ◽  
Feedforward Neural Network ◽  
Grinding Process ◽  
Grinding Temperature ◽  
Optimization Scheme ◽  
Wheel Wear ◽  
Simulation Research ◽  
Traverse Grinding

This paper presents an intelligent system for optimization of the cylindrical traverse grinding process whose objective is to maximize the material removal rate with constraints on workpiece out-of-roundness and waviness errors, on surface finish, and on grinding temperature. A theoretical analysis of wheel wear development in the traverse grinding process is presented. Next, the results of an experimental test are discussed to establish the most efficient strategy for grinding allowance removal. In the optimization scheme a feedforward neural network is employed to obtain a model which describes relations between the process input parameters and the grinding results. Then this model is used to optimize adaptively the traverse grinding process. The performance of the proposed optimization system is evaluated by simulation research.

On Scale Correction Model of Coastline and its Application for Coastline Remote Sensing Monitoring

2013 ◽  
Vol 303-306 ◽  
pp. 734-739
Author(s):  
Hua Guo Zhang ◽  
Dong Ling Li ◽  
Ai Qin Shi
Keyword(s):  
Remote Sensing ◽  
High Precision ◽  
Coastal Zone ◽  
Absolute Error ◽  
Correction Method ◽  
Remote Sensing Images ◽  
Correction Model ◽  
Remote Sensing Monitoring ◽  
Multi Scale ◽  
Map Scale

This paper focuses on the scale correction of coastline extracted from remote sensing images. Measurement of coastline is one of the basic and core work of coastal zone remote sensing monitoring projects. Based on analysis of coastline scale effect and multi-scale simulation of coastline, a scale correction method is presented for remote sensing coastline. This method can be used to correct remote sensing coastline to specified map scale, in order to obtain high-precision remote sensing monitoring results of coastline. The results of application example showed that the absolute error of coastline length is reduced to about one third of the original error after correction using the presented method. So the presented method can increase the accuracy of remote sensing coastline for specified scale substantially.

Can syllabification improve pronunciation by analogy of English?

2006 ◽  
Vol 13 (1) ◽  
pp. 1-24 ◽  
Author(s):  
YANNICK MARCHAND ◽  
ROBERT I. DAMPER
Keyword(s):  
Computational Linguistics ◽  
Language Processing ◽  
Speech Synthesis ◽  
Analogical Reasoning ◽  
Written Language ◽  
Speech Technology ◽  
Syllable Boundary ◽  
Boundary Information ◽  
Unknown Words ◽  
Pronunciation By Analogy

In spite of difficulty in defining the syllable unequivocally, and controversy over its role in theories of spoken and written language processing, the syllable is a potentially useful unit in several practical tasks which arise in computational linguistics and speech technology. For instance, syllable structure might embody valuable information for building word models in automatic speech recognition, and concatenative speech synthesis might use syllables or demisyllables as basic units. In this paper, we first present an algorithm for determining syllable boundaries in the orthographic form of unknown words that works by analogical reasoning from a database or corpus of known syllabifications. We call this syllabification by analogy (SbA). It is similarly motivated to our existing pronunciation by analogy (PbA) which predicts pronunciations for unknown words (specified by their spellings) by inference from a dictionary of known word spellings and corresponding pronunciations. We show that including perfect (according to the corpus) syllable boundary information in the orthographic input can dramatically improve the performance of pronunciation by analogy of English words, but such information would not be available to a practical system. So we next investigate combining automatically-inferred syllabification and pronunciation in two different ways: the series model in which syllabification is followed sequentially by pronunciation generation; and the parallel model in which syllabification and pronunciation are simultaneously inferred. Unfortunately, neither improves performance over PbA without syllabification. Possible reasons for this failure are explored via an analysis of syllabification and pronunciation errors.

scholarly journals Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3581
Author(s):  
Rachid Laref ◽  
Etienne Losson ◽  
Alexandre Sava ◽  
Maryam Siadat
Keyword(s):  
Nitrogen Dioxide ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Correction Method ◽  
Climatic Conditions ◽  
Estimation Accuracy ◽  
Calibration Model ◽  
Monitoring Networks ◽  
Correction Model ◽  
Almost All

This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors’ sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.

scholarly journals Evaluation of Emotional Satisfaction Using Questionnaires in Voice-Based Human–AI Interaction

2021 ◽  
Vol 11 (4) ◽  
pp. 1920
Author(s):  
Jong-Gyu Shin ◽  
Ga-Young Choi ◽  
Han-Jeong Hwang ◽  
Sang-Ho Kim
Keyword(s):  
User Satisfaction ◽  
Intelligent Systems ◽  
Evaluation Method ◽  
Intelligent System ◽  
Human Life ◽  
Design Parameters ◽  
Sentence Structure ◽  
Artificial Intelligence Technology ◽  
Satisfaction Evaluation ◽  
The Right

With the development of artificial intelligence technology, voice-based intelligent systems (VISs), such as AI speakers and virtual assistants, are intervening in human life. VISs are emerging in a new way, called human–AI interaction, which is different from existing human–computer interaction. Using the Kansei engineering approach, we propose a method to evaluate user satisfaction during interaction between a VIS and a user-centered intelligent system. As a user satisfaction evaluation method, a VIS comprising four types of design parameters was developed. A total of 23 subjects were considered for interaction with the VIS, and user satisfaction was measured using Kansei words (KWs). The questionnaire scores collected through KWs were analyzed using exploratory factor analysis. ANOVA was used to analyze differences in emotion. On the “pleasurability” and “reliability” axes, it was confirmed that among the four design parameters, “sentence structure of the answer” and “number of trials to get the right answer for a question” affect the emotional satisfaction of users. Four satisfaction groups were derived according to the level of the design parameters. This study can be used as a reference for conducting an integrated emotional satisfaction assessment using emotional metrics such as biosignals and facial expressions.

scholarly journals Remote Monitoring System Based on Artificial Intelligence Technology

2022 ◽  
Vol 2146 (1) ◽  
pp. 012039
Author(s):  
Fanhua Wang ◽  
Jiangli Qu
Keyword(s):  
Remote Monitoring ◽  
Intelligent System ◽  
Information Age ◽  
It Industry ◽  
Remote Monitoring System ◽  
Development Status ◽  
Future Challenges ◽  
Artificial Intelligence Technology ◽  
Smart Tv

Abstract With the advent of the information age, IOTT has been favored by many industries and has become another profound revolution in the IT industry. In such an era, the application of IOTT in IB construction can broaden the practicability of intelligent system, ORA, improve the management and service ability of IB, so as to improve people’s quality of life. This paper expounds the development status and future challenges of IOTH, and analyzes the interactive design of smart TV.

scholarly journals Design of Belarusian and Russian natural language interfaces for online help systems

Informatics ◽  
2021 ◽  
Vol 18 (4) ◽  
pp. 40-52
Author(s):  
S. A. Hetsevich ◽  
Dz. A. Dzenisyk ◽  
Yu. S. Hetsevich ◽  
L. I. Kaigorodova ◽  
K. A. Nikalaenka
Keyword(s):  
Natural Language ◽  
User Interfaces ◽  
Speech Synthesis ◽  
Intelligent System ◽  
Dialogue System ◽  
Natural Language Interfaces ◽  
Voice Input ◽  
Natural Language Interface ◽  
Question And Answer ◽  
Language User

O b j e c t i v e s. The main goal of the work is a research of the natural language user interfaces and the developmentof a prototype of such an interface. The prototype is a bilingual Russian and Belarusian question-and-answer dialogue system. The research of the natural language interfaces was conducted in terms of the use of natural language for interaction between a user and a computer system. The main problems here are the ambiguity of natural language and the difficulties in the design of natural language interfaces that meet user expectations.M e t ho d s. The main principles of modelling the natural language user interfaces are considered. As an intelligent system, it consists of a database, knowledge machine and a user interface. Speech recognition and speech synthesis components make natural language interfaces more convenient from the point of view of usability.R e s u l t s. The description of the prototype of a natural language interface for a question-and-answer intelligent system is presented. The model of the prototype includes speech-to-text and text-to-speech Belarusian and Russian subsystems, generation of responses in the form of the natural language and formal text.An additional component is natural Belarusian and Russian voice input. Some of the data, required for human voice recognition, are stored as knowledge in the knowledge base or created on the basis of existing knowledge. Another important component is Belarusian and Russian voice output. This component is the top required for making the natural language interface more user-friendly.Co n c l u s i o n. The article presents the research of natural language user interfaces, the result of which provides the development and description of the prototype of the natural language interface for the intelligent question- and-answer system.

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