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qnnpack

Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators

quantized_neural_network

The quantization of CNN/LSTM

quantizedneuralnetworks-keras-tensorflow

Quantized Neural Networks - networks trained for inference at arbitrary low precision.

raspberry-pi-kws

A QbyE-KWS Demo runs on Raspberry Pi

really-awesome-gan

A list of papers on Generative Adversarial (Neural) Networks

recommend

recommendation system with python

recommendationsystem

Book recommender system using collaborative filtering based on Spark

recommendersystem-paper

This repository includes some papers that I have read or which I think may be very interesting.

respeaker_for_raspberrypi

Examples to use ReSpeaker series Mic Arrays on Raspberry Pi

rir-generator

Generating room impulse responses

rnnoise-nu

Recurrent neural network for audio noise reduction, slightly improved for general use

rpmusic

基于 Flask 框架搭建的一个播放器，音乐源来自虾米、网易云音乐。在线音乐播放器 http://rpmusic.coding.io/

rspapers

Must-read papers on Recommender System.

scikit-learn

scikit-learn: machine learning in Python

segan

Speech Enhancement Generative Adversarial Network in TensorFlow

seq2seq

A general-purpose encoder-decoder framework for Tensorflow

seq2seq-1

Sequence to Sequence Learning with Keras

simd

C++ image processing library with using of SIMD: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2, AVX-512, VMX(Altivec) and VSX(Power7), NEON for ARM.

simple_kws

GRU based keyword spotting, clean envirnoment

single-word-speech-recognition-using-gmm-hmm-

sound-source-localization

The location of sound source is estimated using an array of microphones in MATLAB using LMS, NLMS and LLMS algorithms

sound_signal_process-matlab-

语音信号处理实验教程（MATLAB源代码）

sparse-winograd-cnn

Efficient Sparse-Winograd Convolutional Neural Networks

speaker-diarization

Speaker diarization scripts, based on AaltoASR

speaker_recognition_gmm_ubm

A speaker recognition system which uses GMM-UBM for use in an Android application which helps in monitoring patients suffering from Schizophrenia.

speakerdiarization_rnn

Speaker diarization problem using Recurrent Neural Network. Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channel).

speakeridentificationneuralnetworks

⇨ The Speaker Recognition System consists of two phases, Feature Extraction and Recognition. ⇨ In the Extraction phase, the Speaker's voice is recorded and typical number of features are extracted to form a model. ⇨ During the Recognition phase, a speech sample is compared against a previously created voice print stored in the database. ⇨ The highlight of the system is that it can identify the Speaker's voice in a Multi-Speaker Environment too. Multi-layer Perceptron (MLP) Neural Network based on error back propagation training algorithm was used to train and test the system. ⇨ The system response time was 74 µs with an average efficiency of 95%.

specaugment

A Implementation of SpecAugment with Tensorflow & Pytorch, introduced by Google Brain

speech-denoising-wavenet

A neural network for end-to-end speech denoising

speech-derev-dnn

Speech dereverberation using deep neural networks