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Speaker recognition method based on convolution neural network and spectrogram

A convolutional neural network and speaker recognition technology, applied in the field of speaker recognition based on convolutional neural network, can solve problems such as difficulty in training and short speech, and achieve the effect of less hardware cost and resources, easy implementation, and simple and fast calculation.

Inactive Publication Date: 2017-07-14
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

Considering that the actual training speech is short, it is difficult to train a GMM model for each speaker separately

Method used

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  • Speaker recognition method based on convolution neural network and spectrogram
  • Speaker recognition method based on convolution neural network and spectrogram
  • Speaker recognition method based on convolution neural network and spectrogram

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Embodiment Construction

[0023] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0024] The speaker audio data set has 24 speakers who read the numbers 0-9 respectively, and the following operations are performed on the speaker audio data set.

[0025] S1 generates a spectrogram operation:

[0026] Step 1: Obtain the sampling frequency, left and right channels by reading the sound signal.

[0027] Step 2: Store these data in an array and calculate the length.

[0028] Step 3: Perform windowing processing on the frequency division data, where the overlap ratio is 50%, and save the data

[0029] Step 4: Perform Fourier transform on the frequency-divided data

[0030] Step 5: Display the spectrogram through an array.

[0031] S2 deep learning stage operation:

[0032] Step 1: Convert the voice signal of the audio file into a spectrogram through code;

[0033] Step 2: After getting these spectrograms, run GenerateTrainAnd...

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Abstract

The invention discloses a speaker recognition method based on a convolution neural network and a spectrogram, and the method comprises the following steps: firstly collecting an audio signal of each speaker; secondly converting the audio signals into the spectrogram; thirdly taking an image as an input layer, and training the neural network through AlexNet training; fourthly adjusting the weight values and biases of all layers of the neural network layer by layer through a reverse propagation algorithm; finally obtaining the parameters of the neural network, and classifying the speakers. The method achieves the quick recognition of the speakers through a convolution neural network processing method.

Description

technical field [0001] The invention belongs to the technical field of speech recognition, and relates to a speaker recognition method based on a convolutional neural network. Background technique [0002] With the development of information technology, high technology has been integrated into our life in the form of digitization, which brings a lot of convenience and also promotes the development of digital life. The identification technology has also undergone tremendous changes, from the traditional password verification method to more emerging technologies such as digital certificates and biometric authentication. Especially biometric technology, because it uses the inherent physiological or behavioral characteristics of the human body as the identification basis for individual verification, overcomes the shortcomings of traditional authentication methods that are easy to be lost, forgotten, and easily counterfeited. extensive attention of researchers at home and abroad...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L17/18G10L17/04
Inventor 李玉鑑穆红章
Owner BEIJING UNIV OF TECH
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