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
Tiny Machine Learning Snoring Detection Model for Embedded devices
An automatic speaker recognition system built from digital signal processing tools, Vector Quantization and LBG algorithm
stm32-speech-recognition-and-traduction is a project developed for the Advances in Operating Systems exam at the University of Milan (academic year 2020-2021). It implements a speech recognition and speech-to-text translation system using a pre-trained machine learning model running on the stm32f407vg microcontroller.
MFCC features + SVM for speech emotion classification
Multi-class audio classification with MFCC features using CNN
Detect alcohol induced intoxication level from a voice sample
Voice Activity Detection and signal segmentation in time windows. Feature extraction in time and frequency domain. Classification in ten individual speakers.
Another project for classifying Covid and non-covid patients through cough sound. Using CRNN-Attention model with the sound data converted into image data
Genre Detection of Bengali Rabindranath Tagore's Song Based On Audio Data.
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
In this challenge, the goal is to learn to recognize which of several English words is pronounced in an audio recording. This is a multiclass classification task.
Voice Activity Detector based on MFCC features and DNN model
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 Recognition deep learning model based on feature extraction from Mel Frequency Cepstral Coefficients
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