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-vad-

about the VAD

aalto-robotics

Grasp Planning, MDP and RL

aubio

a library for audio and music analysis

audio_test

MFCC-STM32

audiomlproject1

Voice Activity Detection: In this first assignment, we will create a dataset that simulates speech in every-day scenarios. We train a classifier on this dataset for distinguishing voiced from non-voiced sections, a task called voice activity detection, VAD for short. This, of course, requires a ground truth in terms of VAD annotations.

audiomlproject2

Speaker Detection: We have one target speaker whom we want to detect. The set of impostors is open, i.e., we have no prior information on the test speakers. An important part of the speaker detection pipeline is voice activity detection to filter out segments of the signal that do not contain speech.

dtw_based_isolated_word_recognition

environmentalsoundclassification

Here, an algorithm to classify environmental sounds with the aim of providing contextual information to devices such as hearing aids for optimum performance is proposed. We use signal sub-band energy to construct signal-dependent dictionary and matching pursuit algorithms to obtain a sparse representation of a signal. The coefficients of the sparse vector are used as weights to compute weighted features. These features, along with mel frequency cepstral coefficients (MFCC), are used as feature vectors for classification. Experimental results show that the proposed method gives an accuracy as high as 95.6 %, while classifying 14 categories of environmental sound using a Gaussian mixture model (GMM). For more details, please refer to [1].

gibsonenv

Gibson Environments: Real-World Perception for Embodied Agents

humantimbre_recognition

This algorithm aims at matching best alike famous singer from test sample based on MFCC parameters and SVM

lstd-voice-activity-detection

lstm

Voice activity detection of noisy speech files with LSTM. LSTM is implemented with Keras. Data processing is done with Python, MATLAB, and Bash. Experiments are done on Johns Hopkins CLSP GPUs.

ltpd-vad

Voice activity detection based on long-term pitch divergence

machine-learning-multinomial-logistic-regression-project

3. Machine Learning Multinomial Logistic Regression Project implemented in MATLAB where six hundred music files dataset is given and all belongs to one of the six music genres given. Based on FFT and MFCC feature calculation of each song, it will be classified into each genre using Multinomial Logistic Regression and respective accuracies will be calculated based on training

mfcc-word-recognition

Signal Processing Course, MFCC with VQ, DTW, HMM, KNN, CNN, etc

mfccemi

Eye movement identification using MFCCs

music_classification_mfcc

nnvad

MLP based Voice Activity Detection

py_vad_tool

python script for voice activity detection.

python-vad

Use python to achieve voice activity detection, this program may be helpful for voice application

python_speech_features

This library provides common speech features for ASR including MFCCs and filterbank energies.

pyvad

VAD(Voice Activity Detector) python 实现对时时读入的流式数据进行端点检测

reinforcement-learning

Implementation of Single-Agent and Multi-Agent Reinforcement Learning Algorithms. MATLAB.

reinforcement-learning-code

reinforcement-learning-with-tensorflow

Simple Reinforcement learning tutorials

rl

Reinforcement learning in python

rlcc

High-performance implementations of several reinforcement learning algorithms and some commonly used benchmark problems (Matlab & C++)

rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

rlsscontinuouscontroltutorial

Tutorial on continuous control at Reinforcement Learning Summer School 2017.

robot