Method for intelligently testing surround sound effect based on Bluetooth sound equipment

Abstract

The invention, which relates to the technical field of digital audio processing, discloses a Bluetooth-sound-based surround sound effect intelligent test method comprising the following steps: collecting sound measurement data at different positions in a plurality of rounds of power enhancement tests; spectral analysis is carried out based on the sound measurement data at different positions in a plurality of rounds of power enhancement tests, and surround sound effect frequency spectrums at different positions in each round of power enhancement test are obtained; analyzing frequency domain coherence between frequency characteristics in the surround sound effect frequency spectrum, and evaluating surround sound effect frequency interaction states at different positions in each round of power enhancement test; based on the change trend of the surround sound effect frequency interaction state at different positions in the power enhancement test, evaluating surround effect indexes of the Bluetooth sound equipment under different powers; and judging whether the surround effect indexes of the Bluetooth sound equipment under different powers meet the ideal range interval of the surround effect of the Bluetooth sound equipment or not. The method has the advantages that the testing efficiency is improved, and the product quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of digital audio processing, and in particular to an intelligent testing method for surround sound effects based on a Bluetooth speaker. Background Art

[0002] Intelligent testing of the surround sound effects of Bluetooth speakers refers to the process of objectively and accurately evaluating the surround sound effects of Bluetooth speakers using intelligent testing methods and equipment.

[0003] The existing surround sound effect is mainly about how to meet the personalized needs of different users, but the actual solution is to choose a neutral surround sound effect that meets the needs of most users. As the hardware of Bluetooth speakers is iterated, the neutral surround sound will gradually fail to meet the needs of most users. Therefore, a surround sound effect solution for Bluetooth speakers in the car market is proposed. Summary of the invention

[0004] In order to solve the above technical problems, an intelligent testing method for surround sound effects based on Bluetooth speakers is provided. This technical solution solves the problem that the above-mentioned existing surround sound effects mainly meet the personalized needs of different users, but the actual solution is to select a neutral surround sound effect that satisfies the vast majority of users. Moreover, with the hardware iteration of Bluetooth speakers, the neutral surround sound will gradually fail to satisfy the vast majority of users.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A surround sound effect intelligent testing method based on Bluetooth speakers, comprising:

[0007] Obtain a standard surround sound test audio file, perform several rounds of power enhancement tests on surround distributed Bluetooth speakers, and collect audio measurement data at different positions in the several rounds of power enhancement tests;

[0008] Performing spectrum analysis based on the sound measurement data at different positions in several rounds of power enhancement tests to obtain the surround sound frequency spectrum at different positions in each round of power enhancement tests;

[0009] Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum is analyzed to evaluate the interaction state of the surround sound frequency at different positions in each round of power enhancement test;

[0010] Based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect indicators of Bluetooth speakers at different powers are evaluated;

[0011] It is determined whether the surround effect index of the Bluetooth speaker at different powers meets the ideal range of the surround sound effect of the Bluetooth speaker. If so, it is determined to be normal; if not, it is determined to be abnormal.

[0012] Preferably, performing spectrum analysis based on the sound measurement data at different positions in several rounds of power enhancement tests to obtain the surround sound frequency spectrum at different positions in each round of power enhancement tests specifically includes:

[0013] Based on the acoustic measurement data at different positions in several rounds of power enhancement tests, data is divided according to the acoustic measurement data at different positions under the same power, and an acoustic measurement data matrix A of several positions under several rounds of power is constructed;

[0014]

[0015] Among them, a ij is the acoustic measurement data of the jth position at the i-th power, m is the total number of power enhancement tests, and n is the total number of acquisition positions;

[0016] Standardizing each element in the acoustic measurement data matrix of several positions based on several rounds of power, and converting the acoustic measurement data into acoustic measurement frequency domain data using a discrete Fourier algorithm;

[0017] According to the sound measurement frequency domain data of several positions in each round of power, the surround sound frequency spectrum of different positions in each round of power enhancement test is constructed;

[0018] The discrete Fourier algorithm is specifically:

[0019]

[0020] In the formula, a′ ij is the frequency domain data of the sound measurement at the jth position of the i-th power, is the complex exponential function.

[0021] Preferably, based on the surround sound frequency spectrum at different positions in each round of power enhancement test, analyzing the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum, and evaluating the surround sound frequency interaction state at different positions in each round of power enhancement test specifically includes:

[0022] Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are analyzed;

[0023] According to the cross state of the auto-power spectrum density and the cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum, the mutual coherence coefficient between the surround sound frequencies at different positions is calculated, and the coherence state curve diagram of the surround sound frequency spectrum is constructed;

[0024] The auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are specifically:

[0025]

[0026] In the formula, G xx (f) and G yy (f) is the auto-power spectrum density of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum, G xy (f) is the cross power spectral density of the frequency domain signal in the surround sound frequency spectrum, T is the time length of the surround sound frequency spectrum, E is the average value of the mathematical expectation random variable, x(f,t) is the Fourier transform of the frequency signal x under t unit time, and y(f,t) is the Fourier transform of the frequency signal y under t unit time;

[0027] The mutual coherence coefficient between the surround sound frequencies at different positions is specifically:

[0028]

[0029] In the formula, γ xy (f) is the coherence coefficient of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum at frequency f.

[0030] Preferably, based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect index of the Bluetooth speaker under different powers is evaluated, which specifically includes:

[0031] Based on the coherence state curve diagram of the surround sound frequency spectrum, marking the anti-coherent distorted frequency domain signal in the coherence state curve diagram, and constructing the coherence distortion state curve diagram of the surround sound frequency spectrum;

[0032] Based on the coherent distortion state curve diagram of the surround sound frequency spectrum, the positive coherent and anti-coherent frequency signals are marked according to the unit time, which are recorded as the positive and negative spectrum signal time series data of the surround sound frequency spectrum;

[0033] Based on AR autoregression, a surround sound state evaluation model for speakers is constructed;

[0034] The power of several rounds during the test is used as the influence condition of the surround sound effect of the sound system;

[0035] According to the influence conditions of the surround sound effect of the audio system, the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum are substituted into the surround sound effect state evaluation model of the audio system, and a number of powers are used as independent variables, and the coherent distortion states of the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum at a number of different positions are used as dependent variables;

[0036] Based on the entropy weight method, weights are assigned to the coherent distortion states of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at several different positions, and the surround effect index for evaluating the Bluetooth speaker at different powers under the distortion state is calculated.

[0037] Among them, the surround sound status evaluation model of the speaker is specifically as follows:

[0038]

[0039] Where D j (t) is the coherent distortion state of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at the jth position under t unit time, β ij is the regression coefficient of the i-th round power to the j-th position coherent distortion state, P i is the power in the i-th round of testing, α kj (t) is the kth lagged regression coefficient of the jth position under t unit time, S j (tk) is the positive and negative spectrum signal of the surround sound frequency spectrum at the jth position under tk unit time, ∈ j (t) is the error term of the jth position in t unit time;

[0040] Among them, the surround effect indicators of Bluetooth speakers at different power levels are as follows:

[0041]

[0042] In the formula, R ij is the surround effect index of the Bluetooth speaker at the jth position at the ith power, W D is the weight of the Dth coherent distortion state.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention proposes an intelligent test scheme for surround sound effects based on Bluetooth speakers. This scheme obtains standard surround sound test audio files, performs multiple rounds of power enhancement tests on Bluetooth speakers, and collects audio measurement data at different locations for spectrum analysis, thereby evaluating the frequency domain coherence and interaction state change trend in the surround sound frequency spectrum, and finally determining whether the surround effect of the Bluetooth speaker at different powers meets the ideal range. The beneficial effect is that the surround sound state of the Bluetooth speaker can be accurately evaluated, the test efficiency can be accelerated, and the product quality can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flow chart of an intelligent testing method for surround sound effects based on Bluetooth speakers;

[0046] Figure 2 A flow chart of a method for obtaining a frequency spectrum of surround sound;

[0047] Figure 3 A flow chart of a method for evaluating the frequency interaction state of surround sound;

[0048] Figure 4 Flowchart of the method for evaluating the surround effect index of Bluetooth speakers at different power levels. DETAILED DESCRIPTION

[0049] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0050] Reference Figure 1 As shown, a surround sound effect intelligent testing method based on Bluetooth speakers includes:

[0051] Obtain a standard surround sound test audio file, perform several rounds of power enhancement tests on surround distributed Bluetooth speakers, and collect audio measurement data at different positions in the several rounds of power enhancement tests;

[0052] Performing spectrum analysis based on the sound measurement data at different positions in several rounds of power enhancement tests to obtain the surround sound frequency spectrum at different positions in each round of power enhancement tests;

[0053] Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum is analyzed to evaluate the interaction state of the surround sound frequency at different positions in each round of power enhancement test;

[0054] Based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect indicators of Bluetooth speakers at different powers are evaluated;

[0055] It is determined whether the surround effect index of the Bluetooth speaker at different powers meets the ideal range of the surround sound effect of the Bluetooth speaker. If so, it is determined to be normal; if not, it is determined to be abnormal.

[0056] This solution obtains standard surround sound test audio files, performs multiple rounds of power enhancement tests on Bluetooth speakers, and collects audio measurement data at different locations for spectrum analysis, thereby evaluating the frequency domain coherence and interaction state change trend in the surround sound frequency spectrum, and ultimately determining whether the surround effect of the Bluetooth speaker at different powers meets the ideal range. The beneficial effect is that it can accurately evaluate the surround sound status of the Bluetooth speaker, accelerate test efficiency, and improve product quality.

[0057] Reference Figure 2 As shown, based on the sound measurement data at different positions in several rounds of power enhancement tests, spectrum analysis is performed to obtain the surround sound frequency spectrum at different positions in each round of power enhancement tests, specifically including:

[0058] Based on the acoustic measurement data at different positions in several rounds of power enhancement tests, data is divided according to the acoustic measurement data at different positions under the same power, and an acoustic measurement data matrix A of several positions under several rounds of power is constructed;

[0059]

[0060] Among them, a ij is the acoustic measurement data of the jth position at the i-th power, m is the total number of power enhancement tests, and n is the total number of acquisition positions;

[0061] Standardizing each element in the acoustic measurement data matrix of several positions based on several rounds of power, and converting the acoustic measurement data into acoustic measurement frequency domain data using a discrete Fourier algorithm;

[0062] According to the sound measurement frequency domain data of several positions in each round of power, the surround sound frequency spectrum of different positions in each round of power enhancement test is constructed;

[0063] The discrete Fourier algorithm is specifically:

[0064]

[0065] In the formula, a′ ij is the frequency domain data of the sound measurement at the jth position of the i-th power, is the complex exponential function.

[0066] It is understandable that since the sound measurement data collected by the simulated human ear test head at different positions is time domain data including amplitude and frequency, but the sound measurement data changes discontinuously, the discrete Fourier algorithm is used to convert the sound measurement time domain data into sound measurement frequency domain data, which can more intuitively observe and analyze the frequency components of the surround sound.

[0067] Reference Figure 3 As shown, based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum is analyzed, and the interaction state of the surround sound frequency at different positions in each round of power enhancement test is evaluated, which specifically includes:

[0068] Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are analyzed;

[0069] According to the cross state of the auto-power spectrum density and the cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum, the mutual coherence coefficient between the surround sound frequencies at different positions is calculated, and the coherence state curve diagram of the surround sound frequency spectrum is constructed;

[0070] The auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are specifically:

[0071]

[0072] In the formula, G xx (f) and G yy (f) is the auto-power spectrum density of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum, G xy (f) is the cross power spectral density of the frequency domain signal in the surround sound frequency spectrum, T is the time length of the surround sound frequency spectrum, E is the average value of the mathematical expectation random variable, x(f,t) is the Fourier transform of the frequency signal x under t unit time, and y(f,t) is the Fourier transform of the frequency signal y under t unit time;

[0073] The mutual coherence coefficient between the surround sound frequencies at different positions is specifically:

[0074]

[0075] In the formula, γ xy (f) is the coherence coefficient of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum at frequency f.

[0076] This solution analyzes the frequency spectrum of surround sound in power enhancement test in detail, calculates the auto-power spectrum density and cross-power spectrum density, and then quantifies the coherence between the sound frequencies at different positions. Finally, the coherence state curve diagram is used to intuitively display the interaction state, providing quantitative parameters for the surround sound state of the test speaker.

[0077] Reference Figure 4 As shown in the figure, based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect indicators for evaluating Bluetooth speakers at different powers include:

[0078] Based on the coherence state curve diagram of the surround sound frequency spectrum, marking the anti-coherent distorted frequency domain signal in the coherence state curve diagram, and constructing the coherence distortion state curve diagram of the surround sound frequency spectrum;

[0079] Based on the coherent distortion state curve diagram of the surround sound frequency spectrum, the positive coherent and anti-coherent frequency signals are marked according to the unit time, which are recorded as the positive and negative spectrum signal time series data of the surround sound frequency spectrum;

[0080] Based on AR autoregression, a surround sound state evaluation model for speakers is constructed;

[0081] The power of several rounds during the test is used as the influence condition of the surround sound effect of the sound system;

[0082] According to the influence conditions of the surround sound effect of the audio system, the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum are substituted into the surround sound effect state evaluation model of the audio system, and a number of powers are used as independent variables, and the coherent distortion states of the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum at a number of different positions are used as dependent variables;

[0083] Based on the entropy weight method, weights are assigned to the coherent distortion states of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at several different positions, and the surround effect index of the Bluetooth speaker at different powers under the distortion state is calculated;

[0084] Among them, the surround sound status evaluation model of the speaker is specifically as follows:

[0085]

[0086] Where D j (t) is the coherent distortion state of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at the jth position under t unit time, β ij is the regression coefficient of the i-th round power to the j-th position coherent distortion state, P i is the power in the i-th round of testing, α kj (t) is the kth lagged regression coefficient of the jth position under t unit time, S j(tk) is the positive and negative spectrum signal of the surround sound frequency spectrum at the jth position under tk unit time, ∈ j (t) is the error term of the jth position in t unit time.

[0087] Among them, the surround effect indicators of Bluetooth speakers at different power levels are as follows:

[0088]

[0089] In the formula, R ij is the surround effect index of the Bluetooth speaker at the jth position at the ith power, W D is the weight of the Dth coherent distortion state.

[0090] It should be noted that the weight of the distortion state is weighted according to the deviation size of the distortion;

[0091] This solution analyzes the coherence state of the surround sound frequency spectrum in detail, marks the anti-coherent distortion frequency domain signal, and constructs a coherence distortion state curve. Based on the AR autoregression method, it builds a surround sound state evaluation model for the speaker, takes different powers as independent variables, and takes the coherence distortion state of the positive and negative spectrum signal time series data of surround sound at different positions as the dependent variable, so as to predict the surround effect index of Bluetooth speakers at different powers. It provides accurate data support for the surround sound test of Bluetooth speakers.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent test method for surround sound effect based on Bluetooth speakers, characterized in that: include: Obtain a standard surround sound test audio file, perform several rounds of power enhancement tests on surround distributed Bluetooth speakers, and collect audio measurement data at different positions in the several rounds of power enhancement tests; Performing spectrum analysis based on the sound measurement data at different positions in several rounds of power enhancement tests to obtain the surround sound frequency spectrum at different positions in each round of power enhancement tests; Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum is analyzed to evaluate the interaction state of the surround sound frequency at different positions in each round of power enhancement test; Based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect indicators of Bluetooth speakers at different powers are evaluated; It is determined whether the surround effect index of the Bluetooth speaker at different powers meets the ideal range of the surround sound effect of the Bluetooth speaker. If so, it is determined to be normal; if not, it is determined to be abnormal.

2. According to claim 1, a surround sound effect intelligent testing method based on Bluetooth speakers is characterized in that: Based on the sound measurement data at different positions in several rounds of power enhancement tests, the spectrum of surround sound frequency at different positions in each round of power enhancement tests is obtained, including: Based on the acoustic measurement data at different positions in several rounds of power enhancement tests, data is divided according to the acoustic measurement data at different positions under the same power, and an acoustic measurement data matrix A of several positions under several rounds of power is constructed; Among them, a ij is the acoustic measurement data of the jth position at the i-th power, m is the total number of power enhancement tests, and n is the total number of acquisition positions; Standardizing each element in the acoustic measurement data matrix at a plurality of positions based on a plurality of rounds of power, and converting the acoustic measurement data into acoustic measurement frequency domain data using a discrete Fourier algorithm; Based on the audio measurement frequency domain data of several positions in each round of power, the surround sound frequency spectrum of different positions in each round of power enhancement test is constructed.

3. According to claim 2, a surround sound effect intelligent testing method based on Bluetooth speakers is characterized in that: The discrete Fourier algorithm is specifically: In the formula, a′ ij is the frequency domain data of the sound measurement at the jth position of the i-th power, is the complex exponential function.

4. According to claim 3, a surround sound effect intelligent testing method based on Bluetooth speakers is characterized in that: Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the frequency domain coherence between the frequency characteristics in the surround sound frequency spectrum is analyzed, and the interaction state of the surround sound frequency at different positions in each round of power enhancement test is evaluated, including: Based on the surround sound frequency spectrum at different positions in each round of power enhancement test, the auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are analyzed; According to the cross state of the auto-power spectrum density and the cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum, the mutual coherence coefficients between the surround sound frequencies at different positions are calculated, and the coherence state curve diagram of the surround sound frequency spectrum is constructed.

5. According to claim 4, a surround sound effect intelligent testing method based on Bluetooth speakers is characterized in that: The auto-power spectrum density and cross-power spectrum density of the frequency domain signal in the surround sound frequency spectrum are specifically: In the formula, G xx (f) and G yy (f) is the auto-power spectrum density of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum, G xy (f) is the cross power spectral density of the frequency domain signal in the surround sound frequency spectrum, T is the time length of the surround sound frequency spectrum, E is the average value of the mathematical expectation random variable, x(f,t) is the Fourier transform of the frequency signal x under t unit time, and y(f,t) is the Fourier transform of the frequency signal y under t unit time; The mutual coherence coefficient between the surround sound frequencies at different positions is specifically: In the formula, γ xy (f) is the coherence coefficient of the frequency domain signal x and the frequency signal y at different positions in the surround sound frequency spectrum at frequency f.

6. The method for intelligently testing surround sound effects based on Bluetooth speakers according to claim 5, characterized in that: Based on the changing trend of the surround sound frequency interaction state at different positions in the power enhancement test, the surround effect indicators for evaluating Bluetooth speakers at different powers include: Based on the coherence state curve diagram of the surround sound frequency spectrum, marking the anti-coherent distorted frequency domain signal in the coherence state curve diagram, and constructing the coherence distortion state curve diagram of the surround sound frequency spectrum; Based on the coherent distortion state curve diagram of the surround sound frequency spectrum, the positive coherent and anti-coherent frequency signals are marked according to the unit time, which are recorded as the positive and negative spectrum signal time series data of the surround sound frequency spectrum; Based on AR autoregression, a surround sound state evaluation model for speakers is constructed; The power of several rounds during the test is used as the influence condition of the surround sound effect of the sound system; According to the influence conditions of the surround sound effect of the audio system, the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum are substituted into the surround sound effect state evaluation model of the audio system, and a number of powers are used as independent variables, and the coherent distortion states of the time series data of the positive and negative spectrum signals of the surround sound effect frequency spectrum at a number of different positions are used as dependent variables; Based on the entropy weight method, weights are assigned to the coherent distortion states of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at several different positions, and the surround effect index for evaluating the Bluetooth speaker at different powers under the distortion state is calculated.

7. The method for intelligently testing surround sound effects based on Bluetooth speakers according to claim 6, characterized in that: The surround sound status evaluation model of the speaker is as follows: Where D j (t) is the coherent distortion state of the positive and negative spectrum signal time series data of the surround sound frequency spectrum at the jth position under t unit time, β ij is the regression coefficient of the i-th round power to the j-th position coherent distortion state, P i is the power in the i-th round of testing, α kj (t) is the kth lagged regression coefficient of the jth position under t unit time, S j (tk) is the positive and negative spectrum signal of the surround sound frequency spectrum at the jth position under tk unit time, ∈ j (t) is the error term of the jth position in t unit time; Among them, the surround effect indicators of Bluetooth speakers at different power levels are as follows: In the formula, R ij is the surround effect index of the Bluetooth speaker at the jth position at the ith power, W D is the weight of the Dth coherent distortion state.

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