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10 articles for “Mel Frequency Cepstral Coefficients (MFCC)”
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Voice Recognition Technique using Guassian Mixture Model
Abstract: This paper gives us some of the important information about the methods used for voice recognition system. Voice recognition is the identification of person with the help of characteristic of voice. Voice recognition has scope ranging from access control to forensics. In this system we are able to identify the speaker as well as verification of the speaker take place using feature extraction and feature matching technique using GMM. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 2, 2015 · pp. 12–15 Read article
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Automatic Baby Cry Detector with sleep music player (ABCD)
Abstract: In today’s world, our lives have become moredependent on technology. One problem which caught our eyesis when parents have to leave their wards (aged between 3months to 2 years) alone due to some essential tasks for a shortduration, the baby goes unmonitored. Normally, parents dothis by leaving their child asleep. In many cases, the childwakes up and starts to cry. In absence of loved ones, babiesneed immediate calmness relief. A …
Published in Journal of Mechatronics and Automation · Vol. 10, Issue 1, 2023 · pp. 21–29 Read article
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A New Systematic Approach of Using SVM, KNN, PNN and CNN to Achieve Higher Accuracy for Classification and Recognition of Music Genre
Abstract: In order to overcome challenges like finding songs that are similar, figuring out which cultures would enjoy particular music, conducting surveys, and using music as therapy, classification and recognition of music genres are essential. The expansion of music-related content available online has created new opportunities for the development of music referral systems, which support user communities in searching, finding, sharing, and producing digitally. Our aim is to develop a systematic …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 1–11 Read article
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Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
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Development of Polymer-Based Sensors for Speech Emotion Recognition
Abstract: Traditional SER research often utilizes microphones with polymer components like Diaphragms and Membranes. Within some microphone designs, polymer membranes which plays a crucial role in converting sound pressure into electrical signals. The paper highlights the application (speech emotion recognition) and have tried to find polymer-based sensors. This work further delves deeper, investigating the performance of the CatBoost algorithm for emotion recognition in voice assistants designed for Indian languages. The research …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 268–274 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Optimized Residual Neural Network for Audio Spoof Detection in Speaker Verification Systems
Abstract: The Automatic speaker verification system is a type of biometric technology that utilizes speech to determine if a person is an authentic user or not. Unfortunately, such systems can be susceptible to audio-spoofing attacks. The proposed work deals with this problem of Audio Spoofing by employing Residual Networks to determine if a voice signal is bonafide or not. A comparative study of Mel-frequency Cepstral coefficients (MFCC), Constant Q Cepstral Coefficients …
Published in Current Trends in Signal Processing · Vol. 12, Issue 2, 2022 · pp. 19–32 Read article
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Identification of English Dialects and Emotions using Spectral and Prosodic Features of Speech Signal Processing
Abstract: AbstractIn this paper, the authors have explored speech features to identify English dialects and emotions. A dialect is any distinguishable variety of a language spoken by a group of people. Emotions provide naturalness to speech. Speech database considered for dialect identification task consists of spontaneous speech spoken by male and female speakers. The emotions considered in this study are anger, disgust, fear, happy, neutral and sad. Prosodic and spectral features …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 2, 2013 · pp. 10–17 Read article
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Performance of Speaker Recognition System in Mismatching Speaking Style
Abstract: Analysis of speaker recognition system under different speaking style and mismatch conditions is presented. Generally, in text independent speaker recognition system, the way of speaking style used remains the same in training and testing phase. Whisper speech is generally used quietly to convey secret information or to avoid disturbing others in quiet place, so hearing of speech is limited to nearby listener only. Source of excitation and vocal tractsystem contains …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 58–65 Read article
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Exploiting Phase of Speech Signal for Speaker Recognition
Abstract: Abstract—Performance of speaker recognition system with feature based on temporal phase is presented in this paper. In the state of the art spectral feature, Mel Frequency Cepstal Coefficient (MFCC) only magnitude of the Fourier Transform of speech signal is considered while phase is ignored. The cepstral coefficients extracted from temporal phase (MFTPC) of speech signal are used as features for speaker recognition system. The performance of MFTPC feature is evaluated …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 81–87 Read article