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Audio visual emotion recognition method based on multi-layer boosted HMM

A technology of emotion recognition and emotion, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problem of low recognition rate

Inactive Publication Date: 2013-02-13
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0013] The purpose of the present invention is to propose a multi-layer enhanced HMM voice-visual fusion emotion recognition method in order to solve the problem of low recognition rate in the prior art

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  • Audio visual emotion recognition method based on multi-layer boosted HMM
  • Audio visual emotion recognition method based on multi-layer boosted HMM
  • Audio visual emotion recognition method based on multi-layer boosted HMM

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Embodiment Construction

[0146] The implementation of the method of the present invention will be described in detail below with reference to the drawings and specific embodiments.

[0147] In this example, 5 experimenters (2 males and 3 females) read sentences with 7 basic emotions (happiness, sadness, anger, disgust, fear, surprise, and neutrality) in a Wizard of Oz scene , The camera synchronously records facial expression images and sound data from the front. In the scene script, each emotion has 3 different sentences, and each person repeats each sentence 5 times. The emotional video data of four people is randomly selected as the training data, and the video data of the remaining person is used as the test set. The entire recognition process is independent of the experimenter. Then, the experimental data was re-labeled using the activation-evaluation space rough classification method, that is, the samples were divided into positive and negative categories along the activation axis, and the samples...

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Abstract

The invention provides an audio visual emotion recognition method based on a multi-layer boosted HMM (Hidden Markov Model), which belongs to the field of automatic emotion recognition. An MBHMM (Multi-layer Boosted Hidden Markov Model) sorter comprises three layers of overall sorters, and each layer of overall sorters is formed by combining a plurality of continuous HMM component sorters from left to right. Three characteristic flows, namely voice, facial expression and shoulder motion in an emotion video, are used as inputs of the layers of overall sorters respectively; when the overall sorters are trained, the weight of each sample is updated continuously by an AdaBoost method, and an emphasis is laid on the sample that the overall sorters of the former characteristic flow difficultly recognize when the current layer of overall sorters is trained by using some characteristic flow by the AdaBoost method. Compared with the existing recognition method, with the adoption of the method, the classification accuracy is improved obviously.

Description

Technical field [0001] The invention relates to a multi-channel information fusion emotion recognition method, in particular to a multi-layer enhanced HMM (Multilayer Boosted HMM, HMM) voice-visual fusion emotion recognition method, which belongs to the field of automatic emotion recognition. Background technique [0002] Researchers in various disciplines have done a lot of work in the field of automatic emotion recognition. Emotions can be expressed using discrete category methods (such as the six basic emotion categories proposed by Ekman), or using continuous dimension methods (such as activation-evaluation space methods), or using evaluation-based methods. Facial expressions, voice, body posture and context, and many other features can be used to identify a person's emotional state. Researchers have done a lot of work on single-modal emotion recognition and analysis. [0003] Combining the information of the two channels of speech and vision can improve the accuracy of emoti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/66G06K9/00
Inventor 吕坤贾云得邹文泽张欣
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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