A spatial noise annoyance modeling method based on binaural psychoacoustic parameter difference

Abstract

The application provides a spatial noise annoyance modeling method based on binaural psychoacoustic parameter difference, and the method uses the binaural psychoacoustic parameter difference as a bridge, establishes a spatial noise annoyance model based on noise self annoyance by using multivariate linear regression, and realizes correction of noise self annoyance in the sound source direction, so that the annoyance of noise in different directions is more reasonably and accurately predicted, the use range of the noise annoyance model is widened, the physical mechanism of the spatial noise annoyance is explained, and the application value of the noise annoyance model is enhanced.

Description

Technical Field

[0001] This invention belongs to the field of sound quality technology, specifically relating to a method for modeling spatial noise annoyance based on the difference in binaural psychoacoustic parameters. Background Technology

[0002] In real life, people are typically exposed to various acoustic environments. From a sound quality perspective, the main impact of noise on people is annoyance. When the sound source is directly incident, the transfer functions of both ears and the head affect the level of annoyance. However, outside of this case, when the sound source is directly incident, a relative azimuth angle exists between the person and the direction of the sound source. In this case, the factors affecting the annoyance level are not only the characteristics of the noise itself but also related to the direction of the sound source. In real-world environments, the direction of the sound source has a significant impact on the level of annoyance. When there is an angle between the person and the direction of the sound source, using the noise's inherent annoyance level as the evaluation result is unreasonable and inaccurate.

[0003] In the current technology, the evaluation of annoyance level is mainly based on the annoyance level of the noise itself. A few field questionnaire surveys or studies on the annoyance level of sound events involve the location information of the sound source, but these studies are still relatively preliminary. They do not make a separate and quantitative judgment on the impact of noise location on annoyance level, and they do not conduct further in-depth research on annoyance level and its influencing factors. Summary of the Invention

[0004] To address the problems of existing technologies, this invention proposes a spatial noise annoyance modeling method based on subjective annoyance experiments, using the difference in binaural psychoacoustic parameters as a characteristic parameter. Under different sound source azimuth angles, using the difference in binaural psychoacoustic parameters as a bridge, and based on the annoyance of the noise itself, a spatial noise annoyance model is established using multiple linear regression. This model corrects the annoyance of the noise itself for the sound source azimuth, thereby providing a more reasonable and accurate prediction of the annoyance of noise from different azimuths. This broadens the application scope of the noise annoyance model, facilitates the explanation of the physical mechanism of spatial noise annoyance, and enhances the application value of the noise annoyance model.

[0005] The technical solution of this invention is as follows.

[0006] The method for modeling spatial noise annoyance based on the difference in binaural psychoacoustic parameters includes the following steps.

[0007] Step 1: Record noise samples from different sound source locations.

[0008] Step 2: Calculate the psychoacoustic parameters of the left and right ears of the noise samples obtained in Step 1, and obtain the difference in psychoacoustic parameters between the left and right ears for each noise sample.

[0009] Step 3: Conduct a subjective evaluation experiment on the annoyance level of the noise samples obtained in Step 1.

[0010] Step 4: Establish a multiple linear regression model based on the difference in psychoacoustic parameters between the left and right ears obtained in Step 2 and the annoyance level obtained in Step 3; where the dependent variable of the model is the annoyance level of the noise sample under different sound source orientations, and the independent variables of the model are the difference in psychoacoustic parameters between the left and right ears and the annoyance level of the noise sample itself; the annoyance level of the noise sample itself refers to the annoyance level when the noise source is facing the head in a free field and the sound wave incident direction is the front of the face.

[0011] Furthermore, in step 1, the process of recording noise samples is as follows: in an anechoic chamber, the noise source is directed toward an artificial head wearing binaural microphones, and noise samples are collected when the sound wave incident direction is the front of the artificial head and face, as well as noise samples when the sound wave incident direction is at an angle relative to the front of the artificial head and face.

[0012] Furthermore, the psychoacoustic parameters in step 2 include loudness, sharpness, roughness, and wave intensity.

[0013] Furthermore, the reference sample method was used in the subjective evaluation experiment of annoyance level in step 3.

[0014] Furthermore, in step 3, the reference sample method uses noise samples when the sound wave incident direction is the front of the artificial head and face as reference samples.

[0015] Furthermore, in step 3, when using the reference sample method to evaluate the level of annoyance, the subject hears a pair of sounds each time. Each pair contains two 5-second segments of sound with a 2-second interval in between. The first segment of sound is the reference sound sample, and the second segment of sound is the sample to be evaluated. After listening to each pair of sounds, the subject has 5 seconds to compare the level of annoyance of the second segment of sound with respect to the reference sample and to score it.

[0016] Furthermore, after conducting the annoyance evaluation experiment in step 3, data is removed during data processing based on the results of misjudgment analysis and correlation analysis.

[0017] A method for determining the placement of an air purifier based on annoyance level includes the following steps.

[0018] Step a: Using an air purifier as the noise source, obtain a multiple linear regression model of the annoyance level of the air purifier based on the spatial noise annoyance level modeling method based on the difference in binaural psychoacoustic parameters described above.

[0019] Step b: Place the air purifier in a suitable location within the usage environment. Obtain the difference in psychoacoustic parameters between the left and right ears of the user under normal usage conditions when the air purifier is placed in different locations. Based on the multiple linear regression model of the air purifier's annoyance level obtained in step a, obtain the noise annoyance level of the user under normal usage conditions when the air purifier is placed in different locations. Select the location with the lowest noise annoyance level as the placement location for the air purifier.

[0020] A method for selecting the location of a work rest area within a substation based on annoyance level includes the following steps.

[0021] Step A: For noise sources within the substation area, obtain a multiple linear regression model of the annoyance level of noise sources within the substation area according to the spatial noise annoyance level modeling method based on the difference in binaural psychoacoustic parameters described above.

[0022] Step B: For the selectable work rest locations within the substation area, conduct psychoacoustic tests on the subjects at each location to obtain the difference in psychoacoustic parameters between the left and right ears at each location. Based on the multiple linear regression model of noise source annoyance within the substation area obtained in Step A, obtain the noise annoyance level of the subjects at different locations, and select the location corresponding to the minimum noise annoyance level as the work rest location.

[0023] Beneficial effects.

[0024] 1. This invention provides a new model building method and application for spatial noise assessment, further broadening the scope of application of noise annoyance models. It corrects for the inherent annoyance of noise by using the difference in binaural psychoacoustic parameters, distinguishing the inherent annoyance of noise itself, and the model improves the prediction accuracy of noise annoyance at different azimuth angles in space.

[0025] 2. This invention corrects and predicts the annoyance level of spatial noise, which is beneficial for explaining the physical mechanism. It quantitatively describes the interaural perception difference caused by the sound source azimuth angle using the difference in binaural psychoacoustic parameters, and incorporates the annoyance level of the noise itself into the annoyance level model. The evaluation of noise in space uses psychoacoustic methods to study the influence of the sound source azimuth angle on the physical characteristics of binaural sound signals, determines the contribution of each component, and further judges its impact on annoyance level, making it more reasonable and effective, and revealing a clearer physical mechanism.

[0026] 3. This invention enhances the application value of noise annoyance models. The human ear has different effects on sound sources at different azimuth angles, thus affecting their annoyance levels. In engineering applications, the annoyance level of noise at different azimuth angles can be changed by adjusting the parameters of the left and right ears, providing reference and guidance for engineering applications.

[0027] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0028] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, wherein...

[0029] Figure 1 Flowchart of this invention.

[0030] Figure 2 Diagram showing the initial positions of the dominant and non-dominant ears.

[0031] Figure 3 A schematic diagram of the trajectories of the dominant and non-dominant ears.

[0032] Figure 4 A diagram showing the positions of the dominant and non-dominant ears after rotating 30° clockwise.

[0033] Figure 5 A diagram showing the positions of the dominant and non-dominant ears after rotating 150° clockwise.

[0034] Figure 6 The annoyance level of substation noise at different horizontal deflection angles and its fitting curve.

[0035] Figure 7 Annoyance level of air purifier noise at different horizontal deflection angles and its fitting curve.

[0036] Figure 8 The relative angular annoyance of substation noise under different horizontal deflection angles and its fitted value.

[0037] Figure 9 The relative angular annoyance of air purifier noise at different horizontal deflection angles and its fitted value. Detailed Implementation

[0038] To clearly describe this method and process, we will first explain the relevant terminology and its interpretation.

[0039] Dominant and non-dominant ears: When the distance between the two ears and the sound source is different, the ear that is closer to the sound source in a straight line is defined as the dominant ear, and the other ear is defined as the non-dominant ear.

[0040] Binaural psychoacoustic parameter difference: Psychoacoustic parameters include loudness, sharpness, roughness, and wave intensity. The difference in psychoacoustic parameters between the dominant ear and the non-dominant ear is called the binaural psychoacoustic parameter difference.

[0041] Annoyance level of noise itself: In a free field, the annoyance level when the noise source is facing the head and the sound wave is incident on the face directly.

[0042] Spatial noise annoyance: In a free field, the annoyance level is when the noise source is facing the head, but the incident direction of the sound wave is at an angle relative to the front of the face.

[0043] Relative angular annoyance: The difference between the spatial annoyance and the annoyance of the noise itself under the same noise source is defined as the relative angular annoyance ΔA.

[0044] Based on the above principles, this invention provides a method for modeling spatial noise annoyance based on the difference in binaural psychoacoustic parameters, as follows.

[0045] Step 1: Record noise samples from different sound source locations.

[0046] Step 2: Calculate the psychoacoustic parameters of the left and right ears of the noise samples obtained in Step 1, and obtain the difference in psychoacoustic parameters between the left and right ears for each noise sample.

[0047] Step 3: Conduct a subjective evaluation experiment on the annoyance level of the noise samples obtained in Step 1.

[0048] Step 4: Establish a multiple linear regression model based on the difference in psychoacoustic parameters between the left and right ears obtained in Step 2 and the annoyance level obtained in Step 3; where the dependent variable of the model is the noise annoyance level of the noise sample under different sound source locations, and the independent variables of the model are the difference in psychoacoustic parameters between the left and right ears and the annoyance level of the noise sample itself.

[0049] The embodiments of the present invention are described in detail below. These embodiments select two types of noise with significantly different spectral frequencies and auditory properties: substation noise and air purifier noise. Substation noise has more high-energy line spectrum components, making it sound more tonally intense, while air purifier noise is broadband noise, more audibly similar to white noise. The embodiments are illustrated using a horizontal deflection angle as an example.

[0050] In a semi-anechoic chamber, the noise source was fixed near the wall, with the B&K artificial head facing the source. Binaural microphones were attached to the artificial head, and portable acquisition equipment was used to collect data. A loudspeaker was used as the noise source, playing recorded noise from a substation and an air purifier.

[0051] The sound pressure level of the sound source was adjusted by turning the knob on the power amplifier to achieve sound pressure levels of 50, 60, and 70 dB at the human ear. At the same sound source sound pressure level, with the midpoint of the artificial head as the center, a step size of 15° was selected. The artificial head was rotated clockwise by 15° sequentially to obtain sound samples at different deflection angles θ. The above steps were repeated, and sound samples were recorded in 13 directions with a step size of 15° and θ ranging from 0 to 180° for each sound pressure level of each type of noise. The experiment is illustrated below. Figures 2-5As shown, the solid circle represents the sound source, the dashed circle represents the trajectory of both ears, the solid line symbolizes the head, the black square represents the left ear (dominant hearing ear), and the gray square represents the right ear (non-dominant hearing ear). When the person rotates clockwise, the dark arrow area represents the trajectory of the left ear, and the light arrow area represents the trajectory of the right ear.

[0052] Acquisition equipment: The binaural microphone was HEAD BHS II, and the portable acquisition device used was HEAD SQuadrigaIII.

[0053] Explanation of the subjective evaluation experiment on annoyance level.

[0054] Evaluation Indicators: Research shows that most sound quality studies focus on evaluating sound quality based on factors such as preference or annoyance. Annoyance is frequently used to evaluate the sound quality of noise. This example compares substation noise and air purifier noise at different horizontal deflection angles. Based on the perceived characteristics of the noise, spectral analysis, and the actual environments in which these two types of noise occur, we found that both types of noise evoke feelings of irritability and discomfort, with the subjective perception of the subjects leaning more towards annoyance. Therefore, "annoyance" is used as an indicator to characterize sound quality.

[0055] Evaluation criteria: Annoyance level is rated on a 9-point scale, as shown in Table 1.

[0056] Table 1. Annoyance Level Rating Scale (9 Levels)

[0057]

[0058] Participants: aged 18 to 50 years, hearing tests showed that all participants had hearing thresholds below 15 dB in the frequency range of 125 Hz to 8000 Hz.

[0059] Listening Environment: The subjective evaluation experiment was conducted in a quiet, ordinary room. The room was reasonably arranged and furnished, with soft, appropriately bright lighting. The chairs and headphones were designed to make the participants comfortable and to avoid distracting them. The room was evenly lit, well-ventilated, and odorless. The temperature was between 22 and 24°C, and the relative humidity was between 45 and 55%. The background noise in the room was measured to be 47.5 dB, and with headphones on, the sound was virtually unaffected by external noise.

[0060] Playback Equipment: Sound sample segments were generated by randomly sorting the sound samples using Matlab. These segments were then transmitted via computer to a binaural headphone equalizer using Artemis software, and subsequently played back to the subjects through dynamic high-fidelity stereo headphones. During playback, the computer controlled the playback duration, intervals, and order of the sound samples. This sound playback system fully considers the binaural masking effect, maximizing the ideal listening experience.

[0061] Equipment selected: Binaural headphone equalizer: HEADlab-compatible binaural headphone equalizers labP2; Dynamic high-fidelity stereo headphones: SENNHEISER HD600.

[0062] Each participant heard a pair of sounds, each pair consisting of two 5-second segments with a 2-second interval in between. The first segment served as a reference sound sample, and the second segment served as the sample to be evaluated. After listening to each pair of sounds, participants had 5 seconds to compare the level of annoyance of the second segment relative to the reference sample and to rate it.

[0063] Data processing: Data removal is performed according to the following rules.

[0064] Misjudgment analysis: Judging the consistency of multiple evaluations of the same sound sample by the same subject.

[0065] Correlation analysis: to determine the correlation between multiple evaluations of different sound samples by the same subject.

[0066] After data processing, the spatial noise level and its relative angular noise level results are as follows: Figures 6-9 As shown, a psychoacoustic annoyance model was established, selecting five parameters as independent variables: the annoyance level of the noise itself (A0), the binaural loudness difference (ΔL), the binaural roughness difference (ΔR), the binaural sharpness difference (ΔS), and the binaural wave intensity difference (ΔF). The annoyance level of the sound sample was used as the dependent variable, and a multiple regression analysis was performed. Standardized coefficients were selected to establish a target sound annoyance level model based on psychoacoustic parameters. The annoyance level A of substation noise was obtained. s Annoyance level A of air purifier noise a The models are as follows.

[0067] A s =0.988 A0+0.024ΔL+0.025ΔS-0.043ΔR+0.041ΔF.

[0068] A a =0.936 A0+0.067ΔL+0.042ΔS-0.074ΔR+0.076ΔF.

[0069] This model can predict the annoyance level of noise at different horizontal directions.

[0070] In practical use, the placement of air purifiers and the location of work and rest areas within substations can be determined using the multiple linear regression model of annoyance levels obtained above.

[0071] If the air purifier is placed in a suitable location in the usage environment, the difference in psychoacoustic parameters between the left and right ears of the user under normal use conditions when the air purifier is placed in different locations can be obtained. Based on the multiple linear regression model of the air purifier's annoyance level, the noise annoyance level of the user under normal use conditions when the air purifier is placed in different locations can be obtained. The location corresponding to the minimum noise annoyance level can be selected as the placement location of the air purifier.

[0072] For example, regarding the available work rest locations within a substation, the subjects underwent psychoacoustic testing at various locations to obtain the difference in psychoacoustic parameters between their left and right ears at each location. Based on a multiple linear regression model of the annoyance level of noise sources within the substation, the annoyance level of the subjects at different locations was obtained, and the location corresponding to the minimum annoyance level was selected as the work rest location.

[0073] Therefore, this method provides a new approach to model building for spatial noise assessment. It can correct and predict the annoyance level of noise itself by analyzing changes in interaural physical parameters caused by azimuth variations, and it is also more conducive to explaining the physical mechanisms. Furthermore, it provides reference and guidance for engineering applications.

[0074] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method of modeling spatial noise annoyance based on binaural psychoacoustic parameter differences, characterized by: Includes the following steps: Step 1: Record noise samples from different sound source locations; Step 2: Calculate the psychoacoustic parameters of the left and right ears of the noise samples obtained in Step 1, and obtain the difference in psychoacoustic parameters between the left and right ears for each noise sample; the psychoacoustic parameters include loudness, sharpness, roughness and fluctuation intensity; Step 3: Conduct a subjective evaluation experiment on the annoyance level of the noise samples obtained in Step 1; Step 4: Establish a multiple linear regression model based on the difference in psychoacoustic parameters between the left and right ears obtained in Step 2 and the annoyance level obtained in Step 3; where the dependent variable of the model is the annoyance level of the noise sample under different sound source orientations, and the independent variables of the model are the difference in psychoacoustic parameters between the left and right ears and the annoyance level of the noise sample itself; the annoyance level of the noise sample itself refers to the annoyance level when the noise source is facing the head in a free field and the sound wave incident direction is the front of the face.

2. The method of claim 1, wherein the method is based on binaural psychoacoustic parameter difference. In step 1, the process of recording noise samples is as follows: In an anechoic chamber, the noise source is directed toward an artificial head wearing binaural microphones, and noise samples are collected when the sound wave incident direction is the front of the artificial head and face, as well as when the sound wave incident direction is at an angle relative to the front of the artificial head and face.

3. The spatial noise annoyance modeling method based on the difference in binaural psychoacoustic parameters as described in claim 1, characterized in that: The reference sample method was used in the subjective evaluation of annoyance level in step 3.

4. The spatial noise annoyance modeling method based on the difference in binaural psychoacoustic parameters according to claim 3, characterized in that: In step 3, the reference sample method uses noise samples when the sound wave is incident from the front of the artificial head and face as reference samples.

5. The spatial noise annoyance modeling method based on the difference in binaural psychoacoustic parameters according to claim 4, characterized in that: In step 3, when using the reference sample method to evaluate annoyance, the subject hears a pair of sounds each time, with each pair containing two 5-second segments of sound and a 2-second interval in between. The first sound is the reference sound sample, and the second sound is the sample to be evaluated. After listening to each pair of sounds, the participants have 5 seconds to compare the level of annoyance of the second sound with respect to the reference sample and to rate it.

6. The spatial noise annoyance modeling method based on the difference in binaural psychoacoustic parameters as described in claim 1, characterized in that: After conducting the annoyance assessment experiment in step 3, data is removed during data processing based on the results of misjudgment analysis and correlation analysis.

7. A method for determining the placement of an air purifier based on annoyance level, characterized in that: Includes the following steps: Step a: Using an air purifier as a noise source, obtain a multiple linear regression model of the annoyance level of the air purifier according to any one of claims 1 to 6; Step b: Place the air purifier in a suitable location within the usage environment. Obtain the difference in psychoacoustic parameters between the left and right ears of the user under normal usage conditions when the air purifier is placed in different locations. Based on the multiple linear regression model of the air purifier's annoyance level obtained in step a, obtain the noise annoyance level of the user under normal usage conditions when the air purifier is placed in different locations. Select the location with the lowest noise annoyance level as the placement location for the air purifier.

8. A method for selecting the location of a work rest area within a substation based on annoyance level, characterized in that: Includes the following steps: Step A: For noise sources within the substation area, obtain a multiple linear regression model of the annoyance level of noise sources within the substation area according to the method described in any one of claims 1 to 6. Step B: For the selectable work rest locations within the substation area, conduct psychoacoustic tests on the subjects at each location to obtain the difference in psychoacoustic parameters between the left and right ears at each location. Based on the multiple linear regression model of noise source annoyance within the substation area obtained in Step A, obtain the noise annoyance level of the subjects at different locations, and select the location corresponding to the minimum noise annoyance level as the work rest location.

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