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speech_recognition

Speech recognition module for Python, supporting several engines and APIs, online and offline.

speech_synthesis

A toylike diphone-based concatenative tts for the grammar (CV)+, where C={'m','l','p','k','s'} and V={'a','A'}

speech_tools

Edinburgh Speech Tools

sphinxbase

spiffform

A Javascript / JQuery based WYSIWYG form builder / form editor

sprocket

Voice Conversion Tool Kit

sql-query-processor

A C++ implementation for parsing and executing a number of selection, aggregation, grouping queries with joins on relations.

sqlpp11

A type safe SQL template library for C++

sqlpp11-connector-stl

An experimental SQL connector for containers and streams of the C++ Standard Library

sqxclib

sqxclib is a library to convert SQL (or JSON...etc) data to/from C language. It provides ORM features and C++ wrapper.

stargan-voice-conversion

full tensorflow implementation of the paper: StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks https://arxiv.org/abs/1806.02169

stock-market-prediction-using-natural-language-processing

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

style-transfer-pytorch

Unofficial and Easy Pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]

style-transfer-pytorch-1

Neural style transfer in PyTorch.

style_transfer

(C++) Artistic Style Transfer Using OpenCV

styleblit

StyleBlit is an efficient example-based style transfer algorithm that can deliver high-quality stylized renderings in real-time.

stylegan-art

train stylegan through transfer learning

stylit

Stylit algorithm for example-base stylization

stylized-neural-painting

Official Pytorch implementation of the preprint paper "Stylized Neural Painting", in CVPR 2021.

sumgram

sumgram is a tool that summarizes a collection of text documents by generating the most frequent sumgrams (conjoined ngrams)

suneditor

Pure javascript based WYSIWYG html editor, with no dependencies.

surat

implementation based on "Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion"

syncabook

📖🎧 A tool for creating ebooks with synchronized text and audio (EPUB3 with Media Overlays)

syncnet_python

Out of time: automated lip sync in the wild

synth-me

Basic concatenative text-to-speech implementation in Python

synthesizing_obama_network_training

synthesizingobama

Python 3, Tensorflow 1.4.1 compatible codes of "Synthesizing Obama: Learning Lip Sync from Audio".

synthi-tts

Hackathon project to digitize your own voice and have it speak for you! Fully automated!

table-extract

Locate and extract tables and figures in PDFs