mel-spectrogram
There are 77 repositories under mel-spectrogram topic.
Sharad24/Neural-Voice-Cloning-with-Few-Samples
Implementation of Neural Voice Cloning with Few Samples Research Paper by Baidu
BShakhovsky/PolyphonicPianoTranscription
Recurrent Neural Network for generating piano MIDI-files from audio (MP3, WAV, etc.)
tiberiu44/TTS-Cube
End-2-end speech synthesis with recurrent neural networks
Data-Science-kosta/Speech-Emotion-Classification-with-PyTorch
This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.
spotify/realbook
Easier audio-based machine learning with TensorFlow.
CVxTz/audio_classification
CNN 1D vs 2D audio classification
MycroftAI/sonopy
A simple audio feature extraction library
echocatzh/torch-mfcc
A librosa STFT/Fbank/mfcc feature extration written up in PyTorch using 1D Convolutions.
zzw922cn/LPC_for_TTS
Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm.
rednafi/urban-sound-classification
Urban sound source tagging from an aggregation of four second noisy audio clips via 1D and 2D CNN (Xception)
zafarrafii/Zaf-Python
Zafar's Audio Functions in Python for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
zafarrafii/Zaf-Matlab
Zafar's Audio Functions in Matlab for audio signal analysis: STFT, inverse STFT, mel filterbank, mel spectrogram, MFCC, CQT kernel, CQT spectrogram, CQT chromagram, DCT, DST, MDCT, inverse MDCT.
skanderhamdi/attention_cnn_lstm_covid_mel_spectrogram
Attention-based Hybrid CNN-LSTM and Spectral Data Augmentation for COVID-19 Diagnosis from Cough Sound
adasegroup/OSM-one-shot-multispeaker
Framework for one-shot multispeaker system based on Deep Learning
yoyolicoris/wavenet-like-vocoder
Basic wavenet and fftnet vocoder model.
ddman1101/EDM-subgenre-classifier
Code for "Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features" arXiv:2110.08862, 2021.
monetjoe/pianos
This study converts piano recordings to mel spectrogram and classifies them by SOTA pre-trained neural network backbones in CV. Comparative experiments show that SqueezeNet achieves a best classification accuracy of 92.37%.|该项目将钢琴录音转为为mel频谱图，使用微调后的前沿计算机视觉领域预训练深度学习骨干网络对其进行分类，对比实验可知SqueezeNet作为最优网络正确率可达92.37%
renesemela/masters-thesis-music-autotagging
Master's Thesis: Automatic Tagging of Musical Compositions Using Machine Learning Methods
VisionBrain/Neural_Voice_Cloning
Open Source Implementation of Neural Voice Cloning with Few Audio Samples (Baidu Research)
Keerthiraj-Nagaraj/cough-detection-with-transfer-learning
Cough detection with Log Mel Spectrogram, Wavelet Transform, Deep learning and Transfer learning techniques
goepfert/audio_features
Speech Recognition and Voice Activity Detection using a Convolutional Neural Network Architecture built with Tensorflow.js
mariamkhmahran/gunshot-detection-system
This repository contains the Python code for a audio classification system designed to detect gunshots in urban settings.
mikex86/SonopyJava
Java Implementation of the Sonopy Audio Feature Extraction Library by MycroftAI
baggepinnen/LPVSpectral.jl
Least-squares (sparse) spectral estimation and (sparse) LPV spectral decomposition.
KanikeSaiPrakash/Speech-Emotion-Recognition
Speech Emotion Recognition using Deep Learning
ricardokleinklein/deepMultiSpeech
Deep Multi-Speech model
sh3r4zhassan/Sound-Prediction-and-Cancellation-Model
This Model analyzes and predicts the input sound and then using pretrained ANC systems cancels the input sound.
amirragab-ds/Speech-Emotion-Recognition-in-Tensorflow-Using-CNNs
Speech Emotion Recognition (SER) in Tensorflow using CNNs and CRNNs Based on Mel Spectrograms and Mel Frequency Cepstral Coefficients (MFCCs)
Rumeysakeskin/dtw-compare-audio-files
Compute the MFCCs and measure (dis)similarity between two audio files using DTW
zafarrafii/Zaf-Julia
Zafar's Audio Functions in Julia for audio signal analysis: STFT, inverse STFT, CQT kernel, CQT spectrogram, CQT chromagram, MFCC, DCT, DST, MDCT, inverse MDCT.
anirudhs123/Music-Instrument-Classification
In this project we use a Lightweight-CNN based model to classify instruments from the Freesound audio data set. We make use of Mel-Spectrogram features from the input audio data as the input to the CNN model. To add robustness to the model, we use a novel data augmentation technique based on the Cut-Mix algorithm.
cschen1205/cs-mel-spectrogram
Convert audio file to melgram (that is, mel-spectrogram) in .NET
RBGTOP/Music-Genre-Recognition
Music genre classification using deep learning
SimpleKidd/Fault-Diagnosis-of-a-Rotor-Bearing-System-using-ML
Analyzing Vibrational Data of the System using Machine Learning
awal-ahmed/AudioViT
This repository contains different CNN methods for audio classification. It starts with canceling noise from audio. Then it converts the audio into a mel-spectrogram and trains with CNN models.