Machadowisck's starred repositories
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
speech-emotion-ptbr
Classification of emotions based on speech prosody (intonation, rythm, stress) in Portuguese
audiocraft
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.
professional-programming
A collection of learning resources for curious software engineers
cpp-libface
Fastest auto-complete in the east
element-web
A glossy Matrix collaboration client for the web.
huggingsound
HuggingSound: A toolkit for speech-related tasks based on Hugging Face's tools
DeepSpeech
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
brasil.gov.portal
Implementação em Plone do Portal Padrão da Identidade Digital de Governo
portuguese-bert
Portuguese pre-trained BERT models
gappy-mwes
Code for NAACL 2019 paper: "Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions"
pizzadedados
O primeiro e mais querido podcast sobre ciência de dados no Brasil
datascience-pizza
🍕 Repositório para juntar informações sobre materiais de estudo em análise de dados e áreas afins, empresas que trabalham com dados e dicionário de conceitos
CMU-MultimodalSDK-Tutorials
This is a short tutorial for using the CMU-MultimodalSDK.
Voice_Emotion
Detecting emotion in voices
Voice-Emotion-Detector
Voice Emotion Detector that detects emotion from audio speech using one dimensional CNNs (convolutional neural networks) using keras and tensorflow on Jupyter Notebook.
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.
CycleTransGAN-EVC
CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer
spectrogram-soul
speech emotion recognition using Audio Spectrogram Transformer on resd dataset
Speaker-VGG-CCT
Official implementation of the paper "SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers, 2022"