Voice Activity Detection based on Deep Learning & TensorFlow
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Updated
Mar 24, 2023 - Python
Voice Activity Detection based on Deep Learning & TensorFlow
Audio feature extraction and classification
Repository for CIKM 2020 resource track paper: MAEC: A Multimodal Aligned Earnings Conference Call Dataset for Financial Risk Prediction
Detect alcohol induced intoxication level from a voice sample
Using a raspberry pi, we listen to the coffee machine and count the number of coffee consumption
A RESTFUL API implementation of an authentification system using voice fingerprint
Classify music in two categories progressive rock and non-progressive rock using mfcc features, MLP, and CNN.
A repos for USTH Digital Signal Processing 2020 Group 3 project. It's quite obvious in the title.
Speaker Identification System built using mfcc, delta features and streamlit for web-based application.
Open-source Repository for PyMAiVAR software suit.
Audio classification using a simple SVM classifier making use of MFCC and Spectrogram features coded from scratch
Implementation of Mel-Frequency Cepstral Coefficients (MFCC) extraction
Project I carried out during my Machine Learning course in the Master.
Deep learning-based audio spoofing attack detection experiments for speaker verification.
Identify speaker from given speech signal using MFCC features and Gaussian Mixture Models
A machine learning model is trained to determine the word in an audio file
Penerapan metode Random Forest dalam klasifikasi Genre Musik menggunakan ekstraksi fitur MFCC.
RespireNet is an innovative web-based application that harnesses the capabilities of deep learning and Mel-frequency cepstral coefficients (MFCC) as a feature extraction technique for accurate respiratory disease prediction. The primary objective of this user-friendly web application is to facilitate early detection.
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