szhaomsft Goto Github PK

ad-nerf

This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".

api-ai-english-asr-model

Api.ai English Speech Recognition (ASR) Model for Kaldi

asr-server

FastCGI support for Kaldi ASR

automatic-prosody-annotation

awesome-chatbot

Awesome Chatbot Projects,Corpus,Papers,Tutorials.

azure-docs

Open source documentation of Microsoft Azure

bark

🚀 BARK INFINITY 🎶 Power Up The Bark Text-prompted Generative Audio Model

boost-for-android

Android port of Boost C++ Libraries

cntk

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

cognitive-speech-srsample

Community samples to use Cognitive SR services

concentus

Pure Portable C# and Java implementations of the Opus audio codec

concentus.oggfile

Implementing support for reading/writing .opus audio files using Concentus

contextualloss

The Contextual Loss

corert

This repo contains CoreRT, a .NET Core runtime optimized for AOT (ahead of time compilation) scenarios, with the accompanying compiler toolchain.

cortanaskillskit

Create with the Cortana Skills Kit.

crepe

CREPE: A Convolutional REpresentation for Pitch Estimation -- pre-trained model (ICASSP 2018)

ctc_tensorflow_example

CTC + Tensorflow Example for ASR

deepqa

My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

dotnet-docs-samples

.NET code samples used on https://cloud.google.com

experiment

fast-neural-style

Feedforward style transfer

glotthmm

Mirror of GlottHMM

groundhog

Library for implementing RNNs with Theano

honk

PyTorch reimplementation of Google's TensorFlow CNNs for keyword spotting

kaldi-ctc

Connectionist Temporal Classification (CTC) Automatic Speech Recognition

kws

An End-to-End Architecture for Keyword Spotting and Voice Activity Detection

loop

A method to generate speech across multiple speakers

lrucachenet

A fast, generic, thread-safe Least Recently Used (LRU) cache for .NET Standard.

lstm-human-activity-recognition

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

ltfat

This is an official development repository of LTFAT