Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909150
Ganesh P. Prajapat, V. Yadav, Patyasa Bhui
The optimal control of a dynamical system is one of the key ways of control and it is applicable in most of the systems due to its control capability under minimum use of energy. Although a system can be controlled in a classical Proportional-Integral (PI) controller but the optimal control approach drives the system from one state to another state with the minimum time and energy. This is due to its control law based on the minimization of the energy function, popularly known as ‘cost functional’. This paper concentrates on the optimal control of a dynamical system and improvement of its performance in terms of mitigation of the oscillations, overshoot, steady state error and its stability through Linear Quadratic Regulator (LQR). The state-space model of a second-order classical dynamical system has been investigated under optimal control through LQR to improve the system responses and then compared with the PI controller. The efficacy of the proposed LQR control of the system under different disturbances was examined and found its ability to improve the performance of the studied system.
{"title":"Ability Analysis of a Linear Quadratic Regulator for Optimal Control of a Dynamical System","authors":"Ganesh P. Prajapat, V. Yadav, Patyasa Bhui","doi":"10.1109/ASIANCON55314.2022.9909150","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909150","url":null,"abstract":"The optimal control of a dynamical system is one of the key ways of control and it is applicable in most of the systems due to its control capability under minimum use of energy. Although a system can be controlled in a classical Proportional-Integral (PI) controller but the optimal control approach drives the system from one state to another state with the minimum time and energy. This is due to its control law based on the minimization of the energy function, popularly known as ‘cost functional’. This paper concentrates on the optimal control of a dynamical system and improvement of its performance in terms of mitigation of the oscillations, overshoot, steady state error and its stability through Linear Quadratic Regulator (LQR). The state-space model of a second-order classical dynamical system has been investigated under optimal control through LQR to improve the system responses and then compared with the PI controller. The efficacy of the proposed LQR control of the system under different disturbances was examined and found its ability to improve the performance of the studied system.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129711392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pair-trading strategy is an approach that utilizes the fluctuations between prices of a pair of stocks in a short-term time frame, while in the long-term the pair may exhibit a strong association and co-movement pattern. When the prices of the stocks exhibit significant divergence, the shares of the stock that gains at price are sold (a short strategy) while the shares of the other stock whose price falls are bought (a long strategy). This paper presents a cointegration-based approach that identifies stocks listed in the five sectors of the National Stock Exchange (NSE) of India for designing efficient pair-trading portfolios. Based on the stock prices from Jan 1, 2018, to Dec 31, 2020, the cointegrated stocks are identified and the pairs are formed. The pair-trading portfolios are evaluated on their annual returns for the year 2021. The results show that the pairs of stocks from the auto and the realty sectors, in general, yielded the highest returns among the five sectors studied in the work. However, two among the five pairs from the information technology (IT) sector are found to have yielded negative returns.
{"title":"Designing Efficient Pair-Trading Strategies Using Cointegration for the Indian Stock Market","authors":"Jaydip Sen","doi":"10.1063/1.1395242","DOIUrl":"https://doi.org/10.1063/1.1395242","url":null,"abstract":"Pair-trading strategy is an approach that utilizes the fluctuations between prices of a pair of stocks in a short-term time frame, while in the long-term the pair may exhibit a strong association and co-movement pattern. When the prices of the stocks exhibit significant divergence, the shares of the stock that gains at price are sold (a short strategy) while the shares of the other stock whose price falls are bought (a long strategy). This paper presents a cointegration-based approach that identifies stocks listed in the five sectors of the National Stock Exchange (NSE) of India for designing efficient pair-trading portfolios. Based on the stock prices from Jan 1, 2018, to Dec 31, 2020, the cointegrated stocks are identified and the pairs are formed. The pair-trading portfolios are evaluated on their annual returns for the year 2021. The results show that the pairs of stocks from the auto and the realty sectors, in general, yielded the highest returns among the five sectors studied in the work. However, two among the five pairs from the information technology (IT) sector are found to have yielded negative returns.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128207401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909194
Chaitanya Nimbargi, Y. Mane, N. Lokhande
The usage of drones has been increased and they are now being used for safety operations as well as in the security forces. They are being used in military, police forces, in geodesy companies. These applications demand accurate control of the drone, and the drone should follow the desired trajectory accurately so that less errors made in decision making of such complicated application. These applications require that the drones can be controlled using proper controller for controlling the trajectory. They follow the commanded trajectory very accurately while minimizing the error. These controllers get the difference between the actual trajectory and the desired trajectory, that is the error which they try to minimize. In this paper we will discuss about the control of a 2-D quadrotor using a Proportional-Derivative controller and simulate it in MATLAB. The PD controller tries to minimize the error and the derivative of the error. The model takes into account the mass of the drone, the moment of inertia about x-axis, the actual coordinates and the actual roll angle. The errors in this case is the difference between the actual position and the desired position.
{"title":"Control of Quadrotor in 2-D for a Commanded Trajectory","authors":"Chaitanya Nimbargi, Y. Mane, N. Lokhande","doi":"10.1109/ASIANCON55314.2022.9909194","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909194","url":null,"abstract":"The usage of drones has been increased and they are now being used for safety operations as well as in the security forces. They are being used in military, police forces, in geodesy companies. These applications demand accurate control of the drone, and the drone should follow the desired trajectory accurately so that less errors made in decision making of such complicated application. These applications require that the drones can be controlled using proper controller for controlling the trajectory. They follow the commanded trajectory very accurately while minimizing the error. These controllers get the difference between the actual trajectory and the desired trajectory, that is the error which they try to minimize. In this paper we will discuss about the control of a 2-D quadrotor using a Proportional-Derivative controller and simulate it in MATLAB. The PD controller tries to minimize the error and the derivative of the error. The model takes into account the mass of the drone, the moment of inertia about x-axis, the actual coordinates and the actual roll angle. The errors in this case is the difference between the actual position and the desired position.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127185718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908740
P. Raghunathan, Sai Shibu, P. Rekha
Most banking sectors and government entities depend on a centralised mechanism to perform various operations. This mechanism is often slow, inefficient, and unreliable. The Government levies Goods and Service Tax (GST) on the supply of goods and services. GST is a complex multistage indirect tax law applied from manufacturing to the end-user. The current GST implementation has a few loopholes where a seller can easily evade tax payments. Similarly, a Letter of Credit (LC) is a trade process mediated by banking partners. This process is often manual for sharing and validating documents between traders with or within countries for commerce. This paper explores the possibility of implementing GST and LC processes using blockchain technology and aims to address some of the issues faced in the current system. This paper proposes a decentralised application (DApp) to ease the operation logic of GST or e-way bills using smart contracts. The paper also explores a decentralised finance (DeFi) system using blockchain technology to simplify the LC process. This paper also discusses the implementation of the proposed smart contracts on a private blockchain network.
{"title":"Design of Blockchain DApps to Simplify GST and Letter of Credit Processes in Deregulated Financial Services","authors":"P. Raghunathan, Sai Shibu, P. Rekha","doi":"10.1109/ASIANCON55314.2022.9908740","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908740","url":null,"abstract":"Most banking sectors and government entities depend on a centralised mechanism to perform various operations. This mechanism is often slow, inefficient, and unreliable. The Government levies Goods and Service Tax (GST) on the supply of goods and services. GST is a complex multistage indirect tax law applied from manufacturing to the end-user. The current GST implementation has a few loopholes where a seller can easily evade tax payments. Similarly, a Letter of Credit (LC) is a trade process mediated by banking partners. This process is often manual for sharing and validating documents between traders with or within countries for commerce. This paper explores the possibility of implementing GST and LC processes using blockchain technology and aims to address some of the issues faced in the current system. This paper proposes a decentralised application (DApp) to ease the operation logic of GST or e-way bills using smart contracts. The paper also explores a decentralised finance (DeFi) system using blockchain technology to simplify the LC process. This paper also discusses the implementation of the proposed smart contracts on a private blockchain network.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130209233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this project is to develop a system that can predict the price of a cryptocurrency (Bitcoin) based on the sentiment of the input provided. This input will be supplied to the model using the Cryptopanic API, which will extract the latest news related to Bitcoin. These technological advancements can help us make accurate predictions thereby facilitating investments. We have tried to accomplish this by using a series of deep learning techniques and methodologies. Our decision to build this model using LSTM was based on the comparison of results between other algorithms like CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit) and RNN (Recurrent Neural Network). Unlike technical analysis methods which are used for normal stock market prediction we have built a model which will be trained to classify news headlines based on the sentiment detected and give a predicted price. We believe that the use of LSTM to give accurate price prediction would be extremely useful for novice as well as professional Bitcoin traders. Also, it has been proven that public sentiments have been very influential in determining the price of Bitcoin and thus taking that into consideration would improve our understanding and prediction.
{"title":"Bitcoin Price Prediction Using Sentimental Analysis - A Comparative Study of Neural Network Model for Price Prediction","authors":"Karthik Nair, Arham Pawle, Aryan Trisal, Sunantha Krishnan","doi":"10.1109/ASIANCON55314.2022.9908846","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908846","url":null,"abstract":"The goal of this project is to develop a system that can predict the price of a cryptocurrency (Bitcoin) based on the sentiment of the input provided. This input will be supplied to the model using the Cryptopanic API, which will extract the latest news related to Bitcoin. These technological advancements can help us make accurate predictions thereby facilitating investments. We have tried to accomplish this by using a series of deep learning techniques and methodologies. Our decision to build this model using LSTM was based on the comparison of results between other algorithms like CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit) and RNN (Recurrent Neural Network). Unlike technical analysis methods which are used for normal stock market prediction we have built a model which will be trained to classify news headlines based on the sentiment detected and give a predicted price. We believe that the use of LSTM to give accurate price prediction would be extremely useful for novice as well as professional Bitcoin traders. Also, it has been proven that public sentiments have been very influential in determining the price of Bitcoin and thus taking that into consideration would improve our understanding and prediction.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130634890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908951
S. Dhivya, J. Beulah
Character recognition on inscriptions is an area which explores our knowledge of an ancient language. Inscriptions were done in all kinds of environments. This work focuses on recognizing Tamil language characters on stone-based images. From the inscription images, we come to know about the importance of old century languages. Some of the general challenges researchers face in recognizing the characters in stone inscriptions are differentiating the foreground pixel from the background stone images, perspective distortion, different light illumination, the same kind of background/foreground, damaged stones, lack of shape and size of the text. Despite the different ways proposed by the researchers, obstacles and issues continue to exist. This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil. It details the methods applied for preprocessing, feature extraction and classification. It gives a road map for future researchers who wish to carry out research in this area.
{"title":"Ancient Tamil Character Recognition from Stone Inscriptions – A Theoretical Analysis","authors":"S. Dhivya, J. Beulah","doi":"10.1109/ASIANCON55314.2022.9908951","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908951","url":null,"abstract":"Character recognition on inscriptions is an area which explores our knowledge of an ancient language. Inscriptions were done in all kinds of environments. This work focuses on recognizing Tamil language characters on stone-based images. From the inscription images, we come to know about the importance of old century languages. Some of the general challenges researchers face in recognizing the characters in stone inscriptions are differentiating the foreground pixel from the background stone images, perspective distortion, different light illumination, the same kind of background/foreground, damaged stones, lack of shape and size of the text. Despite the different ways proposed by the researchers, obstacles and issues continue to exist. This survey attempts to give a detailed analysis of the recent research works on character recognition from the images of stone inscriptions with a special reference to Tamil. It details the methods applied for preprocessing, feature extraction and classification. It gives a road map for future researchers who wish to carry out research in this area.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125521282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909243
C. Venkatesan, Neeraja Kalarikkal, Y. Bhavya, N. Chilakapati
Electrical Equivalent Model Selection of an Ultracapacitor with its parameter estimated with sufficient accuracy provides an easy mechanism for predicting electrical behavior of the Ultracapacitor under various load conditions, and aids in the overall system design. This paper presents a study and comparison of several Ultracapacitor models through experimental and simulation results. A 650 F Ultracapacitor of Maxwell make is used for the present study. Experimental results obtained with constant current charge discharge tests and Electrochemical Impedance Spectroscopy (EIS) tests are used for validating the performance of the models selected for the study. The Model performance results presented can aid in the selection of the model based on the application.
{"title":"Investigation on Ultracapacitor Characterization and Modeling","authors":"C. Venkatesan, Neeraja Kalarikkal, Y. Bhavya, N. Chilakapati","doi":"10.1109/ASIANCON55314.2022.9909243","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909243","url":null,"abstract":"Electrical Equivalent Model Selection of an Ultracapacitor with its parameter estimated with sufficient accuracy provides an easy mechanism for predicting electrical behavior of the Ultracapacitor under various load conditions, and aids in the overall system design. This paper presents a study and comparison of several Ultracapacitor models through experimental and simulation results. A 650 F Ultracapacitor of Maxwell make is used for the present study. Experimental results obtained with constant current charge discharge tests and Electrochemical Impedance Spectroscopy (EIS) tests are used for validating the performance of the models selected for the study. The Model performance results presented can aid in the selection of the model based on the application.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126526359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9909447
Malhar Bangdiwala, Rutvik Choudhari, Adwait Hegde, A. Salunke
Fantasy Premier League is an ever-growing game, with millions of people playing the game. To outperform the rest, it is imperative for the players to accurately predict the expected points the footballer would earn over the course of the match. However, doing so is not easy as there are several aspects to consider as well as the human bias towards the players’ favourite footballers and teams. This paper attempts to build and compare three machine learning models to accurately predict the number of points that each footballer would earn over the course of the season. For doing so, the Linear Regression, Decision Tree, and Random Forest algorithms have been leveraged. Features such as fixture difficulty, form of the two teams, creativity, and threat of the footballer have been considered. This would help the players of this game to make more informed decisions while making their respective teams.
{"title":"Using ML Models to Predict Points in Fantasy Premier League","authors":"Malhar Bangdiwala, Rutvik Choudhari, Adwait Hegde, A. Salunke","doi":"10.1109/ASIANCON55314.2022.9909447","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909447","url":null,"abstract":"Fantasy Premier League is an ever-growing game, with millions of people playing the game. To outperform the rest, it is imperative for the players to accurately predict the expected points the footballer would earn over the course of the match. However, doing so is not easy as there are several aspects to consider as well as the human bias towards the players’ favourite footballers and teams. This paper attempts to build and compare three machine learning models to accurately predict the number of points that each footballer would earn over the course of the season. For doing so, the Linear Regression, Decision Tree, and Random Forest algorithms have been leveraged. Features such as fixture difficulty, form of the two teams, creativity, and threat of the footballer have been considered. This would help the players of this game to make more informed decisions while making their respective teams.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Depression is a common phenomenon affecting more than 264 million people worldwide. It is one of the leading causes of disability and a major contributor to the overall global burden of disease. Around twice as many women are affected by mental illness compared to men. This situation has worsened during the pandemic. The need to balance both work life and personal life has put them under immense pressure. Even though the diagnosis of mental illness almost exclusively depends on doctor-patient communication, it has its own set of disadvantages such as patient denial, recall bias, subjective biases, time-consuming and inaccuracy and it is a long-term health problem that needs to be continuously monitored and managed. Considering this social problem, we have planned to develop an Emotional Support Mobile application UNWIND – using modern technological concepts of machine learning and artificial intelligence. Which focuses especially on working women and would include several functionalities: a Chabot to detect mental health status in real-time and to provide counseling, an internal activities tracker to find the correlation between changes in lifestyle and mental health, an improvement tracker of the user’s current mental state using facial recognition and also Recommendation system with the support group, which recommends the most suitable professional counselors to the user as per their preferences and enabling into the support group to provide with necessary treatments and consultation at greater accuracy.
{"title":"UNWIND – A Mobile Application that Provides Emotional Support for Working Women","authors":"Priyanka Kugapriya, Mayuriya Manohara, Keerthiga Ranganathan, Dineshgaran Kanapathy, A. Gamage, Arshad Anzar","doi":"10.1109/ASIANCON55314.2022.9909084","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909084","url":null,"abstract":"Depression is a common phenomenon affecting more than 264 million people worldwide. It is one of the leading causes of disability and a major contributor to the overall global burden of disease. Around twice as many women are affected by mental illness compared to men. This situation has worsened during the pandemic. The need to balance both work life and personal life has put them under immense pressure. Even though the diagnosis of mental illness almost exclusively depends on doctor-patient communication, it has its own set of disadvantages such as patient denial, recall bias, subjective biases, time-consuming and inaccuracy and it is a long-term health problem that needs to be continuously monitored and managed. Considering this social problem, we have planned to develop an Emotional Support Mobile application UNWIND – using modern technological concepts of machine learning and artificial intelligence. Which focuses especially on working women and would include several functionalities: a Chabot to detect mental health status in real-time and to provide counseling, an internal activities tracker to find the correlation between changes in lifestyle and mental health, an improvement tracker of the user’s current mental state using facial recognition and also Recommendation system with the support group, which recommends the most suitable professional counselors to the user as per their preferences and enabling into the support group to provide with necessary treatments and consultation at greater accuracy.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"35 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120917394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-26DOI: 10.1109/ASIANCON55314.2022.9908796
Poojary Sachin, Nisheth Correa, Adithya H Shenoy, Arhan Chand Ballal, P. Mittal
Sound is all about vibration. To make a sound something has to vibrate in human this task is performed by larynx. We humans talk to communicate and convey our feelings to each other. Hence there is increased interest in the field of computer science for acoustics. Various applications like automatic speech recognition, age, gender, prosody, emotion and sentiment recognition from speech signals are paving path for better human machine interaction. In this research paper an attempt has been made to predict gender and emotion from speech signal and a detailed comparison of our four models developed has been presented which highlights the relationship between gender and emotion classification accuracies. Our results have shown that creating separate emotion recognition model for male and female voices generates higher accuracy as compared to single model for both classifiers.
{"title":"Gender and Emotion Classification By Hierarchical Modelling Using Convolutional Neural Network","authors":"Poojary Sachin, Nisheth Correa, Adithya H Shenoy, Arhan Chand Ballal, P. Mittal","doi":"10.1109/ASIANCON55314.2022.9908796","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908796","url":null,"abstract":"Sound is all about vibration. To make a sound something has to vibrate in human this task is performed by larynx. We humans talk to communicate and convey our feelings to each other. Hence there is increased interest in the field of computer science for acoustics. Various applications like automatic speech recognition, age, gender, prosody, emotion and sentiment recognition from speech signals are paving path for better human machine interaction. In this research paper an attempt has been made to predict gender and emotion from speech signal and a detailed comparison of our four models developed has been presented which highlights the relationship between gender and emotion classification accuracies. Our results have shown that creating separate emotion recognition model for male and female voices generates higher accuracy as compared to single model for both classifiers.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121803509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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