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HRTF personalization method based on sparse representation classification

A sparse representation and sparse model technology, applied in the field of HRTF personalization, can solve the problem of low reliability of matching results and achieve good matching results

Active Publication Date: 2019-11-22
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

Therefore, when two-dimensional physiological parameters are used for database matching, the reliability of the matching results is low.

Method used

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  • HRTF personalization method based on sparse representation classification
  • HRTF personalization method based on sparse representation classification
  • HRTF personalization method based on sparse representation classification

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Embodiment Construction

[0033] refer to figure 1 , build a test vector with the physiological parameters of the subject number 063, and form a sparse model with the physiological parameters of the remaining subjects. Take the physiological parameters of any subject as a separate category.

[0034] Step 1: The physiological parameters of the i-th subject constitute A i , all subjects make a new dictionary A=[A m,1 ,A m,2 ,...,A m,n-1 ]∈IR m×(n-1) , where m represents the row vector of a single subject's physiological parameters, and n-1 constitutes the number of subjects in the dictionary.

[0035] The physiological parameter y of subject 063 can be obtained through the linear combination of column vectors in the new dictionary A, so y can be expressed as y=Ax.

[0036] Step 2: Since solving y=Ax is a convex optimization problem, y=Ax is constrained by L1 generic number, as shown in formula (7).

[0037]

[0038] Step 3: Measure the similarity between the test sample and the entire physiolog...

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Abstract

The invention discloses an HRTF personalization method, and particularly relates to an HRTF personalization method based on sparse representation classification. The method comprises the following steps of firstly, sparsifying all tested physiological parameter databases; searching a tested B with the same sparse representation as the physiological parameters of the tested A in a physiological parameter database; and finally, taking the HRTF database of the tested B as the physiological parameter database of the tested A. According to the algorithm, HRTF personalization is achieved through a sparse representation classification method. Compared with an existing physiological parameter matching algorithm, the matching effect of the method is better.

Description

technical field [0001] This paper deals with a HRTF personalization method, especially a HRTF personalization method based on sparse representation classification. Background technique [0002] Head Related Transfer Function (Head Related Transfer Function, HRTF) is used to describe the frequency-domain acoustic transfer function of the sound emitted by the free-field sound source to the ears after being scattered and reflected by the head, auricle, torso and other physiological structures. The physiological structure and size of different individuals are different, and HRTF is closely related to the physiological structure and size, so it is a physical quantity with obvious personal characteristics. [0003] The filtering effects of physiological structures such as the torso, head, and auricle have a more significant impact on the acoustic signal, that is to say, the physiological structure has a more significant impact on HRTF. Therefore, it is natural for people to think...

Claims

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Application Information

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IPC IPC(8): G06F16/25G06K9/62H04S1/00
CPCG06F16/252H04S1/00G06F18/22
Inventor 曾向阳路东东
Owner NORTHWESTERN POLYTECHNICAL UNIV
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