A packaged convolutional voice activity detector for noisy environments.
-
Updated
Jun 15, 2019 - Python
A packaged convolutional voice activity detector for noisy environments.
In this project, I implemented Convolutional Neural Networks on images of melspectrogram of sound files.
Given mel-frequency spectrogram predict whether audio is clean or noisy
Polish bird species recognition - Bird song analysis and classification with MFCC and CNNs. Trained on EfficientNets with final score 0.88 AUC. Women in Machine Learning & Data Science project.
audio classification fastai - Convert audio files into images for classification
Perform three types of feature extraction: STFT, MFCC and MelSpectrogram. Apply CNN/VGG with or without RNN architecture. Able to achieve 95% accuracy.
musical genres binary classification using pytorch.audio and keras
Detecting emotions from audios using neural networks
Using Deep Convolutional Generative Adversarial Networks to generate new spoken digits.
UrbanSound classification using Convolutional Recurrent Networks in PyTorch
This repository is mainly about the classification of music genres of Kaggle music dataset in various forms of data preparation
Learnable STRF, from Riad et al. 2021 JASA
A simple Speaker classifier using Keras
Fall 2021 Introduction to Deep Learning - Homework 3 Part 2 (RNN-based phoneme recognition)
Classifying Music Genre with Urban Sound Dataset, Preprocessing with Librosa and Torch audio, Model made in Tensorflow and PyTorch
Fashion Mnist and "recognize a speaker" datasets were utilized for image classification. For this classification task were tried to apply transfer learning from Mnist Fashion to "Recognize a Speaker" and transfer learning inside of Mnist Fashion.
Signal Processing with Python and Librosa
Music recommendation using neural network
A C++ implementation of stft, melspectrogram and mel_to_stft
Add a description, image, and links to the melspectrogram topic page so that developers can more easily learn about it.
To associate your repository with the melspectrogram topic, visit your repo's landing page and select "manage topics."