International Journal of Computer Applications, 2018
A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with H... more A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with Humane-Machine interaction (HMI) has advanced machine intelligence. An emotion precise HMI is designed by integrating speech processing and machine learning algorithm which is sculpted to formulate an automated smart and secure application for detecting emotions in a household as well as in commercial application. This project presents a study of distinguishing emotions by acoustic speech recognition (ASR) using K-means nearest neighbor (K-NN), a machine learning (ML) technique. The most significant paralinguistic information obtained from spectral features is presented by ASR i.e. by using Mel frequency cepstrum coefficient (MFCC). The most important processing techniques methods include feature extraction, feature selection, and classification of emotions. A customized dataset consisting of speech corpus, simulated emotion samples in the Sanskrit language is used to classify emotions in different emotional classes i.e. happy, sad, excitement, fear, anger and disgust. The emotions are classified using a K-NN algorithm over 2 separate models, based on the soft and high pitch voice. Model 1 and 2 achieved about 72.95% and 76.96% recognition
International Journal For Science Technology And Engineering, 2016
In order to help the visually challenged people, a study has been proposed to help visually impai... more In order to help the visually challenged people, a study has been proposed to help visually impaired person to walk more confidently. The study hypothesizes a smart walking stick that alerts visually-impaired people where obstacles and pit ahead is concerned which will help them in walking without causing injury to them. In this system, ultrasonic sensors, ir sensor, headphone, Arduino controller, Micro sd card adapter are used. The overall aim of the device is to provide a convenient and safe method for the blind to overcome their difficulties in daily life.
International Journal of Computer Applications, 2018
Speech processing (SP) is the latest trend in technology. An intelligent and precise human-machin... more Speech processing (SP) is the latest trend in technology. An intelligent and precise human-machine interaction (HMI) is designed to engineer an automated, smart and secure application for household and commercial application. The existing methods highlight the absence of the speech processing in the under-resourced languages. The novelty of this work is that it presents a study of acoustic speech processing (ASP) using spectral components of Mel frequency cepstrum coefficient (MFCC) of Sanskrit language. A customized speech database is created as no generic database is available in Sanskrit. The processing method includes speech signal isolation, feature selection and extraction of selected features for applications. The speech is processed over a custom dataset consisting of Sanskrit speech corpus. The spectral features are calculated over 13 coefficients providing improved performance. The results obtained highlight the performance of the proposed system with the variation of the ...
International Journal of Computer Applications, Jun 15, 2018
A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with H... more A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with Humane-Machine interaction (HMI) has advanced machine intelligence. An emotion precise HMI is designed by integrating speech processing and machine learning algorithm which is sculpted to formulate an automated smart and secure application for detecting emotions in a household as well as in commercial application. This project presents a study of distinguishing emotions by acoustic speech recognition (ASR) using K-means nearest neighbor (K-NN), a machine learning (ML) technique. The most significant paralinguistic information obtained from spectral features is presented by ASR i.e. by using Mel frequency cepstrum coefficient (MFCC). The most important processing techniques methods include feature extraction, feature selection, and classification of emotions. A customized dataset consisting of speech corpus, simulated emotion samples in the Sanskrit language is used to classify emotions in different emotional classes i.e. happy, sad, excitement, fear, anger and disgust. The emotions are classified using a K-NN algorithm over 2 separate models, based on the soft and high pitch voice. Model 1 and 2 achieved about 72.95% and 76.96% recognition
International Journal of Computer Applications, 2018
A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with H... more A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with Humane-Machine interaction (HMI) has advanced machine intelligence. An emotion precise HMI is designed by integrating speech processing and machine learning algorithm which is sculpted to formulate an automated smart and secure application for detecting emotions in a household as well as in commercial application. This project presents a study of distinguishing emotions by acoustic speech recognition (ASR) using K-means nearest neighbor (K-NN), a machine learning (ML) technique. The most significant paralinguistic information obtained from spectral features is presented by ASR i.e. by using Mel frequency cepstrum coefficient (MFCC). The most important processing techniques methods include feature extraction, feature selection, and classification of emotions. A customized dataset consisting of speech corpus, simulated emotion samples in the Sanskrit language is used to classify emotions in different emotional classes i.e. happy, sad, excitement, fear, anger and disgust. The emotions are classified using a K-NN algorithm over 2 separate models, based on the soft and high pitch voice. Model 1 and 2 achieved about 72.95% and 76.96% recognition
International Journal For Science Technology And Engineering, 2016
In order to help the visually challenged people, a study has been proposed to help visually impai... more In order to help the visually challenged people, a study has been proposed to help visually impaired person to walk more confidently. The study hypothesizes a smart walking stick that alerts visually-impaired people where obstacles and pit ahead is concerned which will help them in walking without causing injury to them. In this system, ultrasonic sensors, ir sensor, headphone, Arduino controller, Micro sd card adapter are used. The overall aim of the device is to provide a convenient and safe method for the blind to overcome their difficulties in daily life.
International Journal of Computer Applications, 2018
Speech processing (SP) is the latest trend in technology. An intelligent and precise human-machin... more Speech processing (SP) is the latest trend in technology. An intelligent and precise human-machine interaction (HMI) is designed to engineer an automated, smart and secure application for household and commercial application. The existing methods highlight the absence of the speech processing in the under-resourced languages. The novelty of this work is that it presents a study of acoustic speech processing (ASP) using spectral components of Mel frequency cepstrum coefficient (MFCC) of Sanskrit language. A customized speech database is created as no generic database is available in Sanskrit. The processing method includes speech signal isolation, feature selection and extraction of selected features for applications. The speech is processed over a custom dataset consisting of Sanskrit speech corpus. The spectral features are calculated over 13 coefficients providing improved performance. The results obtained highlight the performance of the proposed system with the variation of the ...
International Journal of Computer Applications, Jun 15, 2018
A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with H... more A modern development in technology is Speech Emotion Recognition (SER). SER in partnership with Humane-Machine interaction (HMI) has advanced machine intelligence. An emotion precise HMI is designed by integrating speech processing and machine learning algorithm which is sculpted to formulate an automated smart and secure application for detecting emotions in a household as well as in commercial application. This project presents a study of distinguishing emotions by acoustic speech recognition (ASR) using K-means nearest neighbor (K-NN), a machine learning (ML) technique. The most significant paralinguistic information obtained from spectral features is presented by ASR i.e. by using Mel frequency cepstrum coefficient (MFCC). The most important processing techniques methods include feature extraction, feature selection, and classification of emotions. A customized dataset consisting of speech corpus, simulated emotion samples in the Sanskrit language is used to classify emotions in different emotional classes i.e. happy, sad, excitement, fear, anger and disgust. The emotions are classified using a K-NN algorithm over 2 separate models, based on the soft and high pitch voice. Model 1 and 2 achieved about 72.95% and 76.96% recognition
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Papers by Sujay Kakodkar