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about the VAD
Grasp Planning, MDP and RL
a library for audio and music analysis
MFCC-STM32
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.
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.
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].
Gibson Environments: Real-World Perception for Embodied Agents
This algorithm aims at matching best alike famous singer from test sample based on MFCC parameters and SVM
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.
Voice activity detection based on long-term pitch divergence
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
Signal Processing Course, MFCC with VQ, DTW, HMM, KNN, CNN, etc
Eye movement identification using MFCCs
MLP based Voice Activity Detection
python script for voice activity detection.
Use python to achieve voice activity detection, this program may be helpful for voice application
This library provides common speech features for ASR including MFCCs and filterbank energies.
VAD(Voice Activity Detector) python 实现对时时读入的流式数据进行端点检测
Implementation of Single-Agent and Multi-Agent Reinforcement Learning Algorithms. MATLAB.
Simple Reinforcement learning tutorials
Reinforcement learning in python
High-performance implementations of several reinforcement learning algorithms and some commonly used benchmark problems (Matlab & C++)
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
Tutorial on continuous control at Reinforcement Learning Summer School 2017.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.