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Big data speech classification method

A classification method and big data technology, applied in speech analysis, speech recognition, instruments, etc., can solve the problems of high cost of use, large number of big data image classification categories, manual labeling samples, etc., to reduce storage costs and improve classification accuracy high effect

Inactive Publication Date: 2015-06-10
WUHU LERUISI INFORMATION CONSULTING
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Problems solved by technology

However, big data image classification faces difficulties such as the huge number of categories and the huge number of samples that need to be classified.
Linear discriminant analysis is relatively expensive for big data. In order to obtain a certain classification performance, it requires a large number of manually labeled samples.
This greatly increases the development cost of speech classification software, and requires a large number of manually labeled samples

Method used

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Embodiment Construction

[0017] The principles and features of the present invention are described below in conjunction with the accompanying drawings, and the examples given are only used to explain the present invention, and are not intended to limit the scope of the present invention.

[0018] like figure 1 Shown, a kind of big data speech classification method comprises the following steps:

[0019] 1) Collect speech samples as a training set;

[0020] 2) Find the optimal spectrum matrix for big data speech classification;

[0021] 3) Perform spectrum analysis on unlabeled data;

[0022] 4) The frequency band is used to classify the big data speech for the spectrum data.

[0023] Preferably, the search for the optimal spectral matrix of big data speech classification includes the following steps:

[0024] Step 1. Establish a local optimization objective function;

[0025] Step 2, establishing a global optimization objective function;

[0026] Step 3. Using the Fourier transform algorithm: co...

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Abstract

The invention discloses a big data speech classification method. The big data speech classification method comprises the following steps of 1 collecting speed samples as a training set, 2 looking for a big data speech classification optimized frequency spectrum matrix, 3 conducting spectral analysis on unmarked data, and 4 adopting frequency bands to classify big data speeches according to frequency spectrum data. By means of the big data speech classification method, feature information of different speech data can be effectively found under the big data situation, accordingly various relevant data are effectively classified, storage cost in the training process is effectively reduced, and the classification accuracy is higher than the accuracy in the prior art.

Description

technical field [0001] The invention relates to a big data speech classification method. Background technique [0002] With the rapid development of the mobile Internet, more and more smart phones and tablet computers with digital cameras have entered people's lives, and it is easy to generate a large amount of personal voice information. Although it is a common method to manage speech data by using time and directory, it lacks the effective management of speech at the semantic level. Therefore, the supervised learning method is used to obtain the speech classification model by learning the artificially labeled data, and then perform automatic speech classification on the unlabeled speech. Since the feature dimension of speech is usually very high, the Fourier transform method can help improve the recognition performance. [0003] Traditional global linear Fourier transform methods are mainly based on linearity, among which linear discriminant analysis is widely used in pa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/08
Inventor 高辉尚成辉
Owner WUHU LERUISI INFORMATION CONSULTING
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