preciden's starred repositories
pihole-blocklist
blocklist for pihole
Speech-Emotion-Recognition-through-Ensemble-Learning
Emotion recognition can be arduous for machine learning algorithms, especially when a multitude of test samples are input from various people. A way to combat this could be the use of ensemble learning. Ensemble learning allows for a combination of multiple machine learning algorithms to come to the most accurate conclusion based upon multiple predictions. In this paper, we devise a method of emotion recognition using ensemble learning of multiple machine learning algorithms from: k-nearest neighbors (KNN), multilayer perceptron (MLP), and convolutional neural networks (CNN). A combination of these relatively accurate algorithms can establish a versatile model for emotion recognition that classifies a plethora of input data. Using ensemble learning, we were able to create a generalized and accurate model for emotion recognition. Using the collection of emotional speech recordings, following a template like the RAVDESS speech data set. Our hybrid model using ensemble learning was able to achieve accuracy ratings of up to 84.2% on the given data set.
Speech_emotion_recognition_BLSTM
Bidirectional LSTM network for speech emotion recognition.
Speech-Emotion-Recognition-using-ML-and-DL
Project Made during Virtual Summer Internship under leadingindia.ai and BENNETT UNIVERSITY.
Emotion-Recognition-in-Hindi-Speech
Classifying utterances in Hindi speech in one of the 8 emotional states (anger, fear, disgust, neutral, sad, happy, surprise, sarcastic) in spoken speech in Hindi
Speech-emotion-recognition-Emo-DB
a SER project using CNN+BiLSTM training on Emo-DB
speech_emotion_recognition
How to detect emotions from speech using Bi-directional LSTM networks and attention mechanism in Keras.
speech_emotion_recognition
In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM).
Speech-Emotion-Analysis
Human emotions are one of the strongest ways of communication. Even if a person doesn’t understand a language, he or she can very well understand the emotions delivered by an individual. In other words, emotions are universal.The idea behind the project is to develop a Speech Emotion Analyzer using deep-learning to correctly classify a human’s different emotions, such as, neutral speech, angry speech, surprised speech, etc. We have deployed three different network architectures namely 1-D CNN, LSTMs and Transformers to carryout the classification task. Also, we have used two different feature extraction methodologies (MFCC & Mel Spectrograms) to capture the features in a given voice signal and compared the two in their ability to produce high quality results, especially in deep-learning models.
Speech-Emotion-Recognition
Recognising Emotion from speech signal with the help of a CNN-LSTM model
speech_emotion_detection
This is a speech emotion detection system using CNN+LSTM layers, built using TensorFlow 2.0.
Speech-Emotion-Recognition-with-Librosa
Building a Speech Emotion Recognition system that detects emotion from human speech tone using Scikit-learn library in Python
Speech-emotion-recognition
An ensemble deep learning approach using CNN-LSTM architecture for binary classifications ensembled using a multilayer perceptron for recognising 7 different categories of emotion from speech
Speech-Emotion-Recognition
The objective of this Deep Learning model is to recognize the emotions from speech.
Speech-Emotion-Recognition-Using-Deep-CNN
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
pi-hole-android-private-dns
Script to auto-install & configure Android Private DNS For Pi-Hole
Speech-Emotion-Recognition-Using-LSTM
This project studies how the performance of LSTM varies according to the different loss functions in the emotion prediction process.
Introduction-to-TensorFlow-for-Artificial-Intelligence-Machine-Learning-and-Deep-Learning-Coursera
This repository contains the assignments for the Coursera course Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning.
Tensorflow-in-practise-Specialization
Four Courses Specialization Tensorflow in practise Specialization
DeepLearning.AI-TensorFlow-Developer-Course
DeepLearning.AI TensorFlow Developer Professional Certificate -Coursera
Deep-Learning-Specialization-Coursera
A deep learning specialization series of 5 courses offered by Andrew Ng at Coursera
deep-learning-coursera
Deep Learning Specialization by Andrew Ng on Coursera.
Deep-Learning-Coursera
Deep Learning Specialization by Andrew Ng, deeplearning.ai.
coursera-deep-learning
Solutions to all quiz and all the programming assignments!!!
VancedManager
Vanced Installer