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caffe-speaker-recognition's Introduction

Caffe-Speaker-Recognition

Convolutional Neural Network to recognize the speaker from a spoken number dataset.

##Dataset The dataset includes audio spectrogram of 24 different speakers, speaking 0-9 numbers. Training set has the total of 3500 records and Testing set includes the total of 1080 records. Dataset Link http://pannous.net/spoken_numbers.tar

##Model Convolutional Neural Network consists of 5 convolution layers, 3 fully connected layers with ReLu and Max-Pooling in between.

##Deep Learning Platform Used Caffe

##Training Steps Executed the following command from Caffe root folder to train the model.

build/tools/caffe train --solver = speaker_recognition/solver.prototxt

##Accuracy Achieved 99% accuracy in 5000 iterations.

##Classification Executed the following command from Caffe root folder for classification the "0_Karen_160.png" which is a spectrogram of user "Karen" speaking number '0' by using the trained model.

build/examples/cpp_classification/classification.bin speaker_recognition/numbers_deploy.prototxt speaker_recognition/numbers_iter_5212.caffemodel speaker_recognition/train_mean.binaryproto speaker_recognition/synset_numbers.txt speaker_recognition/0_Karen_160.png

##Reference https://github.com/pannous/caffe-speech-recognition

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