Results 101 to 110 of about 10,198 (208)

Analisis Variasi Jumlah Fitur MFCC pada LSTM dalam Klasifikasi Suara Aksen Berbahasa Inggris

, 2022
Numerous research have been performed to classify English accents using both classic and contemporary classification methods. In general, past research on voice classification and voice recognition employs the MFCC approach to extract voice features ...
Sharif, Afriandy
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Using Reversed MFCC and IT-EM for Automatic Speaker Verification [PDF]

, 2012
This paper proposes text independent automatic speaker verification system using IMFCC (Inverse/ Reverse Mel Frequency Coefficients) and IT-EM (Information Theoretic Expectation Maximization).
Sania Bhatti, Tariq Jamil Saifullah Khanzada, Sheeraz Memon   +2 more
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Automatic Speech Recognition and Verification using LPC, MFCC and SVM

, 2015
Speech has much capability as an interface between human and computer which comes under the Human Computer interaction (HCI). The major challenge has been the nature of voice is ever varying speech signal. The paper presents the development of the speech
Janvale, Ganesh B., Deshmukh, Ratnadeep R., Oirere, Aaron M.   +2 more
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IMPLEMENTASI MFCC & CNN PADA GENDER VOICE RECOGNITION

Penelitian mengembangkan sistem Gender Voice Recognition menggunakan kombinasi Mel-Frequency Cepstral Coefficients (MFCC) untuk ekstraksi fitur dan Convolutional Neural Networks (CNN) untuk klasifikasi suara berdasarkan gender.
NUGROHO, HARDI TRI
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HSD-Net: a dual-branch CNN-BiLSTM network with hybrid cepstral fusion for heart sound classification. [PDF]

Front Med Technol
Hua C, Tian Y, Li L, Zhou X.
europepmc   +1 more source

MFCC-VQ Approach For QalqalahTajweed Rule Checking

, 2014
In this paper, we investigate the speech recognition system for Tajweed Rule Checking Tool. We propose a novel Mel-Frequency Cepstral Coefficient andVector Quantization (MFCC-VQ) hybridalgorithm to help students to learn and revise proper Al-Quran ...
Ismail, Ahsiah, Mohamed Noor, Noorzaily, Mohd Yusoff, Zulkifli, Idna Idris, Mohd Yamani, Razak, Zaidi   +4 more
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Hybrid CNN-embedding fusion with MFCC-SVM for speech emotion recognition: Random vs actor-wise evaluation on CREMA-D. [PDF]

PLoS One
Kumari P, Raghav YY, Kochher V, Katta PK, A A, M P, A J, Belete FG.   +7 more
europepmc   +1 more source

A Sensor-Based TinyML Acoustic Monitoring System for Edge-Side Animal Sound Recognition on Resource-Constrained Microcontrollers. [PDF]

Sensors (Basel)
Wang Z, Yu G.
europepmc   +1 more source

MAP prediction of pitch from MFCC vectors for speech reconstruction

, 2008
This work proposes a method of predicting pitch and voicing from mel-frequency cepstral coefficient (MFCC) vectors. Two maximum a posteriori (MAP) methods are considered.
Xu Shao, Ben Milner
core  

Non-Invasive Voice-Based Early Detection of Parkinson's Disease via Spectral Feature Analysis and Machine Learning Techniques. [PDF]

Bioengineering (Basel)
Varela-Arellano YO, Soto-Murillo MA, Alcalá-Ramírez V, Villagrana-Bañuelos KE, Salas-Rodriguez LR, Cepeda-Argüelles A, Villagrana-Bañuelos R, Galván-Tejada JI, Arceo-Olague JG, Galván-Tejada CE.   +9 more
europepmc   +1 more source