899 Open source projects that are alternatives of or similar to Emotion Recognition Using Speech

Deep learning codes and projects using Python

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Official PyTorch implementation of paper "A Hybrid Compact Neural Architecture for Visual Place Recognition" by M. Chancán (RA-L & ICRA 2020) https://doi.org/10.1109/LRA.2020.2967324

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

a delightful machine learning tool that allows you to train, test, and use models without writing code

NLP tutorial

📢 Ready to learn or review your knowledge!

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Machine learning, in numpy

Spying using Smartwatch and Deep Learning

Komputation is a neural network framework for the Java Virtual Machine written in Kotlin and CUDA C.

TensorFlow and Deep Learning Tutorials

Anomaly detection for temporal data using LSTMs

🥕 Evolutionary Neural Networks in JavaScript

This repo provides projects on deep-learning mainly using Tensorflow 2.0

An Echo State Network module for PyTorch.

👷‍♂️ A simple package for extracting useful features from character objects 👷‍♀️

Julia port of the Python autograd package.

Machine Learning inference engine for Microcontrollers and Embedded devices

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

mlmodels : Machine Learning and Deep Learning Model ZOO for Pytorch, Tensorflow, Keras, Gluon models...

Deep Learning for Julia

🎨 Color recognition & classification & detection on webcam stream / on video / on single image using K-Nearest Neighbors (KNN) is trained with color histogram features by OpenCV.

The first public PyTorch implementation of Attentive Recurrent Comparators

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

machine learning and deep learning tutorials, articles and other resources

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Scalable Implementation of Deep CFR and Single Deep CFR

An easy-to-use interface for measuring uncertainty and robustness.

Frame-Recurrent Video Super-Resolution (official repository)

Layer-wise Relevance Propagation (LRP) for LSTMs

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis (official repository)

.NET library for 1D signal processing focused specifically on audio processing

主要是爬虫与数据分析项目总结，外加建模与机器学习，模型的评估。

Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses

A collection of common algorithms and data structures implemented in java, c++, and python.

A collection of research papers on decision, classification and regression trees with implementations.

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

A High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".

A single / multi layer / recurrent neural network written in Golang.

Avalanche: a End-to-End Library for Continual Learning.

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.

Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

🐰 Python lib for remo - the app for annotations and images management in Computer Vision

Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁

Learning the Enigma with Recurrent Neural Networks

A P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

Python Adaptive Signal Processing

A bidirectional LSTM with attention for multiclass/multilabel text classification.