System and Method

Abstract

The system generates noise masks based on user feedback for the vehicle. [Solution] In the system 10, the server includes a determination unit 110 that determines assumed noise features based on vehicle information and an evaluation mask supply unit 120 that supplies at least one first noise mask for evaluation based on the assumed features. The vehicle-side device includes an evaluation acquisition unit 190 that acquires user evaluations for each of the first noise masks for evaluation and a second mask generation unit 160 that generates a second noise mask to be used during actual vehicle operation according to the user evaluation. The evaluation mask supply unit includes a first mask generation unit 122 that generates a plurality of first noise masks, a cluster unit 124 that determines the features of each of the plurality of first noise masks and clusters them into a plurality of clusters based on the respective features, and a selection unit 126 that selects at least one first noise mask for evaluation from the clusters corresponding to the assumed features among the plurality of clusters.

Description

Technical Field

[0001] The present invention relates to a system and a method.

Background Art

[0002] Patent Document 1 describes a noise masking device or the like that reduces discomfort caused by noise by outputting a masking sound that masks the noise. [Prior Art Document] [Patent Document] Patent Document 1 Patent No. 6982828

Summary of the Invention

[0003] In a first aspect of the present invention, there is provided a system including a server and a vehicle-side device, the system including: a determination unit that determines an assumed feature amount of assumed noise based on vehicle type information; an evaluation mask supply unit that supplies at least one evaluation first noise mask based on the assumed feature amount; an evaluation acquisition unit that acquires a user evaluation for each of the evaluation first noise masks; and a second mask generation unit that generates a second noise mask to be used during actual operation of the vehicle according to the user evaluation. The evaluation mask supply unit includes: a first mask generation unit that generates a plurality of the first noise masks; a clustering unit that determines feature amounts of each of the plurality of first noise masks and clusters the plurality of first noise masks into a plurality of clusters based on the respective feature amounts; and a selection unit that selects at least one of the evaluation first noise masks from the cluster corresponding to the assumed feature amount among the plurality of clusters.

[0004] In the above system, the assumed feature amount may be extracted based on a spectrum of a transition frequency region where the peak frequency of the assumed noise transitions.

[0005] In the above system, the evaluation mask supply unit may supply a plurality of the first noise masks that differ in portions other than the assumed feature amount.

[0006] In any of the above systems, the volume of the second noise mask may be louder than the volume of the assumed noise.

[0007] In any of the above systems, the evaluation acquisition unit may acquire the user evaluation by simultaneously reproducing the assumed noise and the first noise mask for evaluation.

[0008] Any of the above systems may have a database containing records of the anticipated noise levels.

[0009] In any of the above systems, the evaluation mask supply unit may acquire a first noise mask that satisfies a predetermined similarity condition with respect to the assumed feature quantity, and identify a cluster containing the acquired first noise mask from the plurality of clusters.

[0010] In any of the above systems, the vehicle-side device comprises the evaluation acquisition unit and the second mask generation unit, and the vehicle-side device may acquire the parameter information of the first noise mask for evaluation transmitted from the server to the vehicle-side device.

[0011] In the system described above, the vehicle-side device includes an in-vehicle device and a mobile terminal, and the mobile terminal may wirelessly communicate the parameter information with the server.

[0012] In any of the above systems, the parameter information of the first noise mask for evaluation may include waveform information that defines at least one of the frequency components and amplitude of the first noise mask for evaluation.

[0013] A second aspect of the present invention provides a method performed by a system comprising a server and a vehicle-side device, wherein the method involves determining assumed feature quantities of expected noise based on vehicle type information, supplying at least one first noise mask for evaluation based on the assumed feature quantities, obtaining user evaluations for each of the first noise masks for evaluation, generating a second noise mask to be used during actual vehicle operation according to the user evaluations, and supplying the first noise masks for evaluation, which comprises generating a plurality of the first noise masks, determining the feature quantities of each of the plurality of first noise masks, clustering them into a plurality of clusters based on the respective feature quantities, and selecting at least one first noise mask for evaluation from the clusters corresponding to the assumed feature quantities among the plurality of clusters.

[0014] It should be noted that the above summary of the invention does not list all the necessary features of the present invention. Furthermore, subcombinations of these features may also constitute an invention. [Brief explanation of the drawing]

[0015] [Figure 1] A first configuration example of the system 10 of this embodiment is shown. [Figure 2] An example of the operation flow of the system 10 according to this embodiment is shown. [Figure 3] A more detailed example of the configuration of the first mask generation unit 122 is shown. [Figure 4] A more detailed example of the configuration of the first mask generation unit 122 is shown below. [Figure 5] This graph shows an example of the clustering results obtained by cluster unit 124. [Figure 6] A second configuration example of the system 10 of this embodiment is shown. [Figure 7] An example of a symbol list 700 used for evaluating the first noise mask in the vehicle-side device 30 of the system 10 of this embodiment is shown. [Figure 8] An example of an input reception screen 800 used for evaluating the first noise mask in the vehicle-side device 30 of the system 10 of this embodiment is shown. [Figure 9] Examples of a computer 2200 in which multiple aspects of the present invention may be embodied in whole or in part are shown. [Modes for carrying out the invention]

[0016] The present invention will be described below through embodiments, but these embodiments are not intended to limit the scope of the claims. Furthermore, not all combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0017] Figure 1 shows a first configuration example of the system 10 of this embodiment. The system 10 can generate a noise mask in response to evaluations from users (drivers, etc.) of vehicles such as electric vehicles. The noise mask may be a synthesized sound output according to the operating state of the vehicle and is used to reduce user discomfort caused by noise generated from equipment such as motors when the vehicle is in operation. The system 10 comprises a server 20 and a vehicle-side device 30.

[0018] Server 20 transmits information to the vehicle-side device 30 for generating a noise mask output by the vehicle. Server 20 may be a computer such as a PC, tablet computer, smartphone, workstation, server computer, or general-purpose computer, or it may be a computer system in which multiple computers are connected. Such a computer system is also a computer in a broad sense. Server 20 may also be implemented by one or more executable virtual computer environments within a computer. Alternatively, Server 20 may be a dedicated computer designed for generating vehicle noise masks, or it may be dedicated hardware realized by dedicated circuitry. When a computer is used, Server 20 is realized by the computer executing a program.

[0019] The server 20 includes a first information acquisition unit 100, a determination unit 110, an evaluation mask supply unit 120, and a first communication unit 130.

[0020] The first information acquisition unit 100 may acquire various information for noise mask generation from a user or the like via an external PC or the like. The first information acquisition unit 100 may acquire the first vehicle information and a plurality of parameter information that defines the characteristics of the first noise mask.

[0021] Here, the first vehicle information may be information indicating the operating state of the vehicle. For example, the first vehicle information may be virtual CAN (Controller Area Network) data indicating the simulated operating state of the vehicle. The first vehicle information, as an example, indicates at least one of the vehicle speed, accelerator opening, and motor rotation speed of the vehicle as the operating state.

[0022] The parameter information may include waveform information that defines at least one of the frequency components and amplitudes of the noise mask. The parameter information may include at least one of the volume information and frequency information of each of one or more source sound sources used for generating the noise mask. The parameter information may be information that identifies one source sound source or a combination of a plurality of source sound sources used for generating the noise mask. Also, the parameter information may be waveform information of a sample sound output from the source sound source. Also, when the source sound source includes a sound source that simulates the engine sound of a gasoline vehicle, the parameter information may include model information related to at least one of the structure and performance of the model vehicle corresponding to the engine sound to be simulated. The model vehicle may be, for example, a vehicle of a specific vehicle type or model name for which the engine sound is to be simulated. The model vehicle may be, for example, a gasoline vehicle, and the noise mask may include, in part, a sound that simulates the engine sound of a gasoline vehicle. The model information may include, as an example, at least one of the engine stroke type, crank angle, upper limit value of the engine rotation speed, and maximum engine torque related to the model vehicle. Note that the parameter information may be one set of data corresponding to one (one type) of noise mask, and the plurality of parameter information may be a plurality of sets of data respectively corresponding to a plurality (a plurality of types) of noise masks.

[0023] The determination unit 110 is connected to the first information acquisition unit 100 and the first communication unit 130. The determination unit 110 determines the expected characteristic quantities of the expected noise based on the vehicle type information. The determination unit 110 may acquire vehicle type information from the user via the first communication unit 130 and acquire expected noise information corresponding to the vehicle type information via the first information acquisition unit 100. The determination unit 110 may determine the expected characteristic quantities of the expected noise for the vehicle corresponding to the vehicle type information based on the vehicle type information and the expected noise information. Here, the vehicle type information may be, for example, information that identifies at least one of the types of vehicles. The vehicle type information may, as an example, be information indicating a specific vehicle type, a specific vehicle name, and at least one of the types of the vehicle's motor.

[0024] The evaluation mask supply unit 120 supplies at least one first noise mask for evaluation based on the assumed feature quantities determined by the determination unit 110. The evaluation mask supply unit 120 includes a first mask generation unit 122, a cluster unit 124, and a selection unit 126.

[0025] The first mask generation unit 122 is connected to the first information acquisition unit 100. The first mask generation unit 122 generates a plurality of first noise masks using the first vehicle information and parameter information.

[0026] The cluster unit 124 is connected to the first mask generation unit 122. The cluster unit 124 may cluster multiple first noise masks into multiple clusters based on their respective feature quantities.

[0027] The selection unit 126 is connected to the determination unit 110 and the cluster unit 124. The selection unit 126 may select a first noise mask for evaluation from among multiple clusters that correspond to assumed features.

[0028] The first communication unit 130 is connected to the selection unit 126 and is connected to the second communication unit 140 of the vehicle-side device 30 by wire or wireless. The first communication unit 130 transmits the parameter information of the first noise mask for evaluation, selected by the selection unit 126, to the vehicle-side device 30 via the communication network.

[0029] The vehicle-side device 30 generates a first noise mask for evaluation using parameter information and receives user evaluation of the first noise mask for evaluation. The vehicle-side device 30 may be an in-vehicle device of the vehicle, and may also include a mobile terminal of the vehicle user. The in-vehicle device may be a device mounted in the vehicle that controls the output of a noise mask in accordance with CAN data communicated via the vehicle network in the vehicle.

[0030] The vehicle-side device 30 may be a computer such as a PC, tablet computer, smartphone, workstation, or general-purpose computer, or it may be a computer system 10 in which multiple computers are connected. Such a computer system is also a computer in a broad sense. Alternatively, the vehicle-side device 30 may be implemented by one or more executable virtual computer environments within the computer. Instead, the vehicle-side device 30 may be a dedicated computer designed for noise mask generation in a vehicle, or dedicated hardware realized by dedicated circuits. When a computer is used, the vehicle-side device 30 is realized by executing a program on the computer.

[0031] The vehicle-side device 30 includes a second communication unit 140, a second information acquisition unit 150, a second mask generation unit 160, an output unit 170, an input unit 180, and an evaluation acquisition unit 190.

[0032] The second communication unit 140 transmits and receives data indicating various types of information with the first communication unit 130. The second communication unit 140 receives parameter information of the first noise mask transmitted from the first communication unit 130.

[0033] The second information acquisition unit 150 is connected to the second communication unit 140. The second information acquisition unit 150 may acquire second vehicle information indicating the operating status of the vehicle. The second information acquisition unit 150 may acquire parameter information of the first noise mask for evaluation transmitted from the server 20 to the vehicle-side device 30 via the second communication unit 140.

[0034] The second mask generation unit 160 is connected to the second information acquisition unit 150. The second mask generation unit 160 may generate a first noise mask for evaluation during evaluation operation, and generate a second noise mask to be used during actual vehicle operation during actual vehicle operation. The second mask generation unit 160 may receive second vehicle information and parameter information for the first noise mask for evaluation from the second information acquisition unit 150, and generate a first noise mask for evaluation. The second mask generation unit 160 generates a second noise mask by acquiring necessary parameter information via the second communication unit 140 in response to user evaluation of the first noise mask for evaluation. Here, the second vehicle information may be the same information as the first vehicle information.

[0035] The output unit 170 is connected to the second mask generation unit 160 and the vehicle speaker 40. The output unit 170 may output (play back) the first noise mask or the second noise mask generated by the second mask generation unit 160 through the vehicle speaker 40 (in-car audio equipment, etc.) mounted in the vehicle. The output unit 170 may amplify the noise mask with an amplifier or the like and output it to the vehicle speaker 40.

[0036] The input unit 180 receives user evaluations of the outputted first noise mask for evaluation from the user. The input unit 180 may receive data indicating the user evaluation via a mouse, keyboard, or touch panel, etc.

[0037] The evaluation acquisition unit 190 is connected to the second communication unit 140, the second mask generation unit 160, and the input unit 180. The evaluation acquisition unit 190 acquires user evaluations for each of the first noise masks for evaluation via the input unit 180. The evaluation acquisition unit 190 may cause the second mask generation unit 160 to set parameter information for the second noise mask according to the user evaluation. Also, if the evaluation acquisition unit 190 re-evaluates the first noise mask according to the user evaluation, it may send the evaluation results to the server 20 via the second communication unit 140.

[0038] Figure 2 shows an example of the operation flow of the system 10 according to this embodiment. The system 10 may initiate at least one step of the operation flow in response to receiving a noise mask recommendation request from the user of the vehicle-side device 30. The request may include at least one of the vehicle type information of the target vehicle and the vehicle user information (information that identifies the user, etc.).

[0039] In the S200, the first information acquisition unit 100 acquires first vehicle information and parameter information. The first information acquisition unit 100 may acquire data as first vehicle information that indicates a predetermined value (for example, 80 km / h or 70% accelerator opening) or a predetermined condition (for example, a condition for accelerating or decelerating between 20 km / h and 100 km / h) for at least one of the following: vehicle speed, accelerator opening, and motor rotation speed. Furthermore, the first vehicle information is not limited to either acceleration or deceleration, but may be acquired as data that indicates a series of operating states of the vehicle (for example, a series of transitions such as the vehicle being stopped, accelerating, being driven at a stable speed, and decelerating).

[0040] The first information acquisition unit 100 may acquire first vehicle information corresponding to user information. The first information acquisition unit 100 may acquire first vehicle information that the user prefers as first vehicle information corresponding to the requesting user (for example, first vehicle information indicating high speed or high acceleration for a user who likes high-speed driving, low speed or low acceleration for a user who likes low-speed driving, first vehicle information corresponding to the user's preferred car model, etc.).

[0041] Furthermore, the first information acquisition unit 100 may acquire first vehicle information corresponding to the vehicle type information included in the request. The first information acquisition unit 100 may acquire one or more pieces of first vehicle information depending on the type of model vehicle (e.g., vehicle type or vehicle name). For example, the first information acquisition unit 100 may acquire first vehicle information corresponding to the vehicle type of the model vehicle (e.g., sedan, sports type, coupe, truck, or bus). The first vehicle information corresponding to the type of model vehicle may be information pre-set by the user of the server 20. The first vehicle information may differ depending on the type of model vehicle; for example, the speed indicated by the vehicle information for a sports type model vehicle is higher than the speed indicated by the vehicle information for other types of vehicles such as trucks. The server 20 may pre-store first vehicle information corresponding to user information or vehicle type information.

[0042] The first information acquisition unit 100 may acquire parameter information corresponding to each of the multiple first noise masks that are generated. The first information acquisition unit 100 may acquire first vehicle information and parameter information from an external PC or the like and store it in the server 20. The first information acquisition unit 100 may update the parameter information in response to an update instruction from a user of the server 20 or periodically. This allows the server 20 to propose the newly updated noise mask to the user of the target vehicle.

[0043] In S210, the first mask generation unit 122 generates multiple first noise masks. The first mask generation unit 122 may generate multiple first noise masks by combining multiple parameter information for one first vehicle information. The first mask generation unit 122 may receive first vehicle information corresponding to the vehicle type information of the requesting user or target vehicle from the first information acquisition unit 100. For example, the first mask generation unit 122 may receive first vehicle information for a model vehicle of the same type as the target vehicle from the first information acquisition unit 100.

[0044] The first mask generation unit 122 may generate acoustic data for multiple first noise masks by combining each of the multiple parameter pieces of information with one first vehicle piece of information. In other words, the first noise mask may generate acoustic data based on the parameter pieces included in the first noise mask, depending on the operating state of a given vehicle. For example, the first mask generation unit 122 may generate the first noise mask using an acoustic model that outputs acoustic data representing the first noise mask in response to the input of parameter pieces and first vehicle pieces of information. The first mask generation unit 122 may generate the first noise mask by outputting sampled sounds from one or more combinations of multiple source sound sources according to the parameter pieces and first vehicle pieces of information. Here, one first vehicle piece of information may be one parameter of the operating state of the vehicle, or it may be a set of multiple parameters of the operating state of the vehicle.

[0045] In S220, the clustering unit 124 clusters multiple first noise masks into multiple clusters. The clustering unit 124 may extract feature quantities from each of the multiple first noise masks and cluster the multiple first noise masks according to the similarity of the feature quantities, etc.

[0046] As an example, the cluster unit 124 may cluster the features of the first noise mask extracted using MFCC (Mel-Frequency Cepstrum Coefficients) using K-means. The cluster unit 124 converts the frequency spectrum obtained by Fourier transforming each first noise mask into an amplitude spectrum and applies a Mel filter bank. The cluster unit 124 can perform a discrete cosine transform on the spectrum after applying the Mel filter bank and extract coefficients of a predetermined dimension (1st to nth (n>1) dimensions) as features from the result of the discrete cosine transform. The number of dimensions n may be predetermined by the user or the like. The cluster unit 124 may further reduce the dimensionality of the features using UMAP (Uniform Manifold Approximation and Projection) or the like.

[0047] The clustering unit 124 may perform clustering by using K-means to take the average of the clusters for the extracted features of the first noise mask and classifying them into a predetermined number of clusters. However, the feature extraction, dimensionality reduction, and clustering methods used by the clustering unit 124 are not limited to these. The clustering unit 124 may associate parameter information, data representing the first noise mask generated from the parameter information (e.g., the acoustic data itself or identification information, etc.), and data representing the cluster to which the first noise mask belongs (e.g., cluster identification information, etc.) and record this information in a database within the clustering unit 124.

[0048] In S230, the determination unit 110 determines the expected characteristic quantities of the expected noise of the vehicle based on the vehicle type information. Note that the order of S230 may be reversed with S210 and S220. The determination unit 110 may search a noise database that records expected noise (noise data) using the vehicle type information indicated by a request from the vehicle-side device 30. The noise database may record information on expected noise in association with vehicle type information. The noise database may record motor-induced noise data during acceleration and deceleration of various vehicle types as expected noise. The noise database may record noise data acquired under operating conditions in which the vehicle information (CAN data such as vehicle speed, accelerator opening, and motor rotation speed) used when acquiring noise data in the actual environment is matched with first vehicle information (virtual CAN data). Alternatively, the first vehicle information may be matched with the vehicle information at the time of noise data acquisition. This makes it possible to make the operating conditions such as acceleration and deceleration conditions the same between the time of noise mask generation and the time of noise data measurement.

[0049] The determination unit 110 may extract features from the acoustic data of the assumed noise in the same way as the feature extraction by the cluster unit 124 in S220. The determination unit 110 may use MFCC to extract features from the acoustic data of the assumed noise as assumed features. For example, the determination unit 110 may cut out the acoustic data of the noise into arbitrary time windows, obtain a frequency spectrum for each cut-out data, and extract the transition range of the peak frequency from each frequency spectrum data and apply MFCC to extract features. With such processing, for example, features defined by a multidimensional vector of M (corresponding to the number of dimensions extracted in the MFCC processing) × N (the number of frequency spectrum acquisition processes performed on the acoustic data. The acoustic data may be divided into this number in the time series direction, and a frequency spectrum may be calculated for each data) are obtained from the acoustic data of the noise. The peak frequency of the assumed noise differs depending on the vehicle type and the type of motor installed, and the peak frequency changes with changes such as the motor rotation speed. For example, as the motor rotation speed increases, the noise frequency also shifts to a higher frequency. The assumed features may, for example, be spectral features in the transition frequency region where the assumed noise peak frequency changes, but are not limited to this; any information that indicates the characteristics of the noise is acceptable. The determination unit 110 may extract assumed noise features focusing only on the transition frequency region. The noise database may record the transition frequency region in association with vehicle information. Alternatively, the noise database may record assumed features of the assumed noise acoustic data in association with vehicle information. In this case, the determination unit 110 may obtain assumed features corresponding to the vehicle information from the noise database.

[0050] In S240, the selection unit 126 selects one or more evaluation first noise masks from a plurality of first noise masks according to the assumed features. The selection unit 126 may identify the cluster to which the assumed features belong among a plurality of clusters. For example, the selection unit 126 may identify the cluster to which the first noise mask most similar to the assumed features belongs among the plurality of first noise masks as the cluster to which the assumed features belong. As an example, the selection unit 126 may calculate the distance (Euclidean distance or Manhattan distance, etc.) between each of the features of the plurality of first noise masks and the assumed features, and identify the cluster to which the first noise mask with the smallest distance belongs as the cluster to which the assumed features belong.

[0051] The selection unit 126 may select one or more first noise masks for evaluation from among a plurality of first noise masks belonging to a specified cluster. The selection unit 126 may randomly select a plurality of first noise masks belonging to a specified cluster for evaluation. This allows the selection unit 126 to select a first noise mask in the cluster to which the assumed features belong that has a higher similarity to the assumed noise in the transition frequency domain, but a lower similarity in other frequency domains. Therefore, the evaluation mask supply unit 120 can supply a plurality of first noise masks that differ in parts other than the assumed features, and can supply a variety of first noise masks that have a masking effect. The first communication unit 130 transmits parameter information indicating the first noise masks for evaluation selected by the selection unit 126 to the second communication unit 140 of the vehicle-side device 30.

[0052] In S250, the vehicle-side device 30 regenerates a first noise mask for evaluation according to the parameter information and the second vehicle information. The second communication unit 140 supplies the parameter information received from the server 20 to the second information acquisition unit 150. The second information acquisition unit 150 may receive the first vehicle information from the server 20 via the second communication unit 140 and acquire the first vehicle information as the second vehicle information. The second information acquisition unit 150 may also acquire virtual CAN data, which shows a simulated operating state of the vehicle prepared in advance by the user, as the second vehicle information. The second information acquisition unit 150 may also acquire CAN data, which shows the operating state of the target vehicle during past actual operation, as the second vehicle information.

[0053] The second mask generation unit 160 generates a first noise mask for each parameter of the first noise mask for evaluation by combining the parameter information of each parameter of the first noise mask for evaluation with the second vehicle information. The second mask generation unit 160 may generate the first noise mask using an acoustic model that outputs acoustic data indicating the first noise mask for evaluation in response to the input of parameter information and second vehicle information. The second mask generation unit 160 may generate the first noise mask for evaluation using the same acoustic model as the acoustic model used in the first mask generation unit 122. The second mask generation unit 160 may generate the first noise mask for evaluation using sample sounds output from one or more combinations of multiple source sound sources in response to the parameter information and second vehicle information. The second mask generation unit 160 may generate the first noise mask for evaluation using the same source sound sources as the source sound sources used in the first mask generation unit 122. The second mask generation unit 160 may have the same configuration as the first mask generation unit 122.

[0054] The output unit 170 may selectively reproduce multiple types of evaluation-grade first noise masks through the vehicle speaker 40. The output unit 170 may simultaneously reproduce the expected noise and the evaluation-grade first noise mask. The output unit 170 may receive information on the expected noise (acoustic data, parameter information, etc.) corresponding to the evaluation-grade first noise mask from the server 20's noise database via the second communication unit 140, and simultaneously reproduce the evaluation-grade first noise mask and the expected noise through the vehicle speaker 40. In addition, the output unit 170 may reproduce information on the target vehicle's noise (acoustic data, etc.) pre-stored in the vehicle-side device 30 as the expected noise through the vehicle speaker 40. By simultaneously reproducing the noise and the first noise mask in this way, the user can evaluate the first noise mask in a state closer to the actual operating environment.

[0055] In S260, the evaluation acquisition unit 190 acquires user evaluations input in accordance with the playback of the first noise mask for evaluation. The evaluation acquisition unit 190 may acquire user evaluations in accordance with the simultaneous playback of the assumed noise and the first noise mask for evaluation. The evaluation acquisition unit 190 may acquire user evaluations by associating them with the first noise mask for evaluation that was played at the time of or immediately before acquiring the user evaluation.

[0056] The evaluation unit 190 may acquire user evaluations indicating scores or preferences (like / dislike) for each first noise mask. The evaluation unit 190 may further acquire user evaluations regarding the volume of each first noise mask (for example, whether the user prefers a volume lower or higher than the playback volume at the time of evaluation). By acquiring the user's volume preferences, the volume of the noise masks can be adjusted appropriately, reducing the time and labor costs associated with volume adjustment. The evaluation unit 190 may also acquire user evaluations indicating an instruction to set one of the multiple first noise masks that have been played back for the target vehicle.

[0057] In S270, the evaluation unit 190 decides whether or not to set one of the first noise masks for evaluation as the second noise mask to be used in the actual operation of the vehicle. If the user evaluation of the first noise masks for evaluation is above a predetermined threshold, the evaluation unit 190 may set the first noise mask with the highest user evaluation as the second noise mask for the target vehicle (YES in Figure 2). Also, if the evaluation unit 190 receives a user evaluation instructing it to set one of the multiple first noise masks for evaluation, it may set the first noise mask indicated by the instruction as the second noise mask for the target vehicle (YES in Figure 2). The evaluation unit 190 may set the parameter information corresponding to the first noise mask to be set in the second mask generation unit 160 so that it is used during the actual operation of the vehicle.

[0058] The evaluation unit 190 may set the parameter information to the second mask generation unit 160 so that the volume of the second noise mask is greater than the expected noise volume. The evaluation unit 190 may adjust the volume parameter of the parameter information so that it is greater than the expected noise volume. The evaluation unit 190 may set the parameter information to the second mask generation unit 160 so that the volume of the second noise mask is greater than the volume of the first noise mask at the time of evaluation, in accordance with the user evaluation of the volume of the first noise mask. This can enhance the masking effect.

[0059] The second mask generation unit 160 may generate a second noise mask during actual vehicle operation based on the set parameter information and third vehicle information indicating the actual operating state of the vehicle. The second mask generation unit 160 may generate the second noise mask in the same manner as the generation of the first noise mask for evaluation. The second mask generation unit 160 may receive CAN data from the actual vehicle operation as third vehicle information, input in real time by the second information acquisition unit 150, generate a second noise mask corresponding to the set parameter information, and output it via the output unit 170.

[0060] The second mask generation unit 160 may generate a second noise mask by subtracting at least a portion of the expected noise from the noise mask generated using the set parameter information. The second mask generation unit 160 may generate a second noise mask by performing a process (filtering, etc.) on the noise mask generated from the set parameter information and third vehicle information indicating the actual operating state of the vehicle to reduce the level (volume) in the transition frequency range of the expected noise.

[0061] Furthermore, the evaluation unit 190 may proceed to S280 if the user evaluations for all first noise masks are below a predetermined threshold (NO in Figure 2). Also, the evaluation unit 190 may proceed to S280 if it receives a user evaluation of re-selection (NO in Figure 2). In this case, the evaluation unit 190 may transmit the evaluation result or information indicating re-selection to the server 20 via the second communication unit 140.

[0062] In S280, the selection unit 126 may randomly re-select multiple first noise masks in the cluster to which the assumed feature quantity identified in S240 belongs. Alternatively, the selection unit 126 may randomly re-select multiple first noise masks from another cluster that has the highest similarity to the cluster to which the assumed feature quantity identified in S240 belongs. Alternatively, the selection unit 126 may randomly re-select other multiple first noise masks from the same cluster to which the assumed feature quantity identified in S240 belongs. Alternatively, the selection unit 126 may re-select one or more first noise masks in order of their similarity to the first noise mask that received the highest evaluation result from the user. The selection unit 126 transmits the parameter information of the re-selected evaluation first noise masks to the vehicle-side device 30, and the vehicle-side device 30 may execute S250-S270.

[0063] Thus, the system 10 of this embodiment can efficiently set noise masks using user evaluations. By selecting a first noise mask for evaluation within a clustered cluster, the system 10 can select a first noise mask for evaluation that is similar to the noise and has a high masking effect. Furthermore, the possibility of recommending only undesirable noise masks that excessively match the noise and make the noise louder can be reduced by using clustering based on the features of the noise's transition frequency domain. In addition, the noise masking approach described above brings the following advantages. That is, the system 10 of this embodiment incorporates user preferences and enables efficient setting of noise masks based on those preferences. This approach alleviates the requirement for precision in adjusting the tone of the noise mask. Conventional noise masking requires strict volume adjustment to avoid causing discomfort to the user. However, the proposed system 10 has a configuration that reflects user preferences in the generation of noise masks, so that noise masks that are inherently less likely to cause discomfort to the user are set. Therefore, there is more leeway regarding the magnitude of the volume setting compared to conventional noise masking. In other words, since the strictness regarding volume adjustment is relaxed, it is possible to reduce the adjustment costs related to setting and operating noise masks. Furthermore, by using the features of the noise transition frequency domain as the cluster identification criterion, system 10 can select noise masks with different features outside the transition frequency domain within the identified clusters, recommending a variety of first noise masks and allowing users to find a noise mask that suits their preferences. In addition, by using virtual CAN data as vehicle information in the evaluation, system 10 allows users to audition noise masks even when the vehicle is not actually operating. Moreover, since the parameter information has a smaller data size compared to the acoustic data recorded from the noise mask itself, transmitting the parameter information between server 20 and vehicle-side device 30 results in superior data transfer efficiency.

[0064] The server 20 does not need to have a cluster unit 124. In this case, the selection unit 126 may select at least one first noise mask whose similarity to the assumed features of the assumed noise is greater than or equal to a predetermined threshold. For example, the selection unit 126 calculates the distance (Euclidean distance or Manhattan distance, etc.) between each of the features of the multiple first noise masks and the assumed features, and selects at least one first noise mask for evaluation whose distance is less than or equal to a predetermined threshold.

[0065] Figure 3 shows a more detailed configuration example of the first mask generation unit 122. The first mask generation unit 122 in Figure 3 generates a first noise mask that simulates the engine sound of a vehicle such as a gasoline car. The first mask generation unit 122 includes an acoustic model unit 300 and a volume adjustment unit 310.

[0066] The acoustic model unit 300 has an acoustic model that generates a noise mask that simulates the sound of a vehicle's engine. The acoustic model unit 300 outputs a noise mask in response to the input of parameter information and first vehicle information to the acoustic model. The acoustic model may be a function that outputs waveform information of the noise mask in response to the input of parameter information and first vehicle information.

[0067] The volume adjustment unit 310 is connected to the acoustic model unit 300. The volume adjustment unit 310 adjusts the volume of the noise mask output by the acoustic model unit 300 according to the parameter information (volume information) and the first vehicle information. The volume adjustment unit 310 outputs the volume-adjusted noise mask as the first noise mask.

[0068] Figure 4 shows another more detailed configuration example of the first mask generation unit 122. The first mask generation unit 122 in Figure 4 generates a first noise mask that does not simulate engine noise. The first mask generation unit 122 includes a plurality of source sound units 400, a plurality of pitch bend loop units 410, a plurality of volume adjustment units 420, and an addition unit 430.

[0069] Multiple source sound units 400-1 to 400-N (where N is an integer greater than or equal to 2) each receive parameter information and output sample sounds according to that information. Each of the multiple source sound units 400 outputs a different sample sound. Each of the multiple source sound units 400 may output short (less than 1 second) sound data. The sample sounds may be, for example, the sounds of orchestral instruments, natural sounds, etc.

[0070] Multiple pitch bend loop units 410-1 to 410-N each receive sample sounds and first vehicle information from source sound units 400-1 to 400-N. Each of the multiple pitch bend loop units 410 extends the output time of the corresponding sample sound by looping it according to the input first vehicle information, and smoothly controls the pitch shift of the sample sound over the extended time.

[0071] Multiple volume adjustment units 420-1 to 420-N each selectively adjust the gain of sampled sounds from multiple pitch bend loop units 410-1 to 410-N according to parameter information and first vehicle information. For example, when the first vehicle information indicates a low speed range, the multiple volume adjustment units 420 make the sampled sound from source sound unit 1 the dominant element, but as the first vehicle information moves to a high speed range, they make the sampled sound from source sound unit 2 the dominant element.

[0072] The summing unit 430 can generate a first noise mask by adding the sample sounds output from multiple volume adjustment units 420.

[0073] The first mask generation unit 122 may have a configuration that combines the configurations shown in Figures 3 and 4. For example, the acoustic model unit 300 and volume adjustment unit 310 in Figure 3 may be added in parallel to the configuration of the first mask generation unit 122 in Figure 4. In this case, the input to the summing unit 430 in Figure 4 may be connected to the output of the volume adjustment unit in Figure 3.

[0074] The second mask generation unit 160 may have the same configuration and operation as the first mask generation unit 122 shown in Figure 3 or Figure 4. Furthermore, the first mask generation unit 122 and the second mask generation unit 160 may be implemented as one or more software modules generated / implemented by the execution of corresponding programs / software by hardware resources included in the server 20 / vehicle-side device 30, respectively. The corresponding programs may include both examples shown in Figures 3 and 4. Additionally, there may be a step prior to the flowchart shown in Figure 2 in which the vehicle-side device 30 downloads the corresponding program from the server 20.

[0075] Figure 5 is a graph showing an example of the clustering results by the clustering unit 124. The vertical and horizontal axes in the graph represent dimensions 1 and 2 of the feature quantities of the first noise mask, respectively. Multiple data points in the graph each represent a feature quantity of the first noise mask. In the example shown in Figure 5, the clustering unit 124 clusters multiple first noise masks into 10 clusters. The selection unit 126 may, for example, randomly select multiple first noise masks 1-5 in cluster 1 to which the assumed feature quantities of the assumed noise belong. The selection unit 126 transmits parameter information corresponding to each of the selected multiple first noise masks 1-5 to the vehicle-side device 30.

[0076] Figure 6 shows a second configuration example of the system 10 of this embodiment. The system 10 of the second configuration example has the same configuration as the system 10 of the first configuration example and may operate in the same manner, except that the vehicle-side device 30 includes the user's mobile terminal 600 of the target vehicle and the in-vehicle device 610 of the target vehicle. The differences from the first configuration example will be mainly described below.

[0077] The mobile terminal 600 wirelessly transmits parameter information of the first noise mask to the server 20 and receives evaluations of the first noise mask from the user. The mobile terminal 600 may be a computer such as a PC, tablet computer, or smartphone. The mobile terminal 600 may have at least some of the functions of the second information acquisition unit 150, the second mask generation unit 160, and the evaluation acquisition unit 190. In the second configuration example, the mobile terminal 600 has a second communication unit 140, a second information acquisition unit 150, a second mask generation unit 620, an output unit 170, a terminal speaker 625, an input unit 180, and an evaluation acquisition unit 190. The second communication unit 140, the second information acquisition unit 150, the output unit 170, and the input unit 180 in the mobile terminal 600 may have the same configuration as in the first configuration example and operate in the same manner. The second mask generation unit 620 may have the same configuration as the second mask generation unit 160 in the first configuration example and may operate in the same manner.

[0078] The terminal speaker 625 may be a speaker mounted on or connected to the mobile terminal 600 and is connected to the output unit 170. The terminal speaker 625 sounds the first noise mask for evaluation generated by the second mask generation unit 620.

[0079] The evaluation unit 190 has the same configuration as the evaluation unit 190 of the first configuration example and may operate in the same manner, except that it is connected to the in-vehicle device 610 wirelessly or via a wired connection. The mobile terminal 600 may store parameter information for the first noise mask determined according to the user evaluation acquired by the evaluation unit 190. For example, the evaluation unit 190 may store parameter information for the first noise mask to be set on the target vehicle, which was determined in S270 according to the user evaluation. The mobile terminal 600 may transmit the stored parameter information to the in-vehicle device 610. For example, the evaluation unit 190 may automatically transmit the stored parameter information to the in-vehicle device 610 when the mobile terminal 600 enters or approaches the target vehicle. As an example, the evaluation unit 190 may automatically transmit the parameter information to the in-vehicle device 610 when the mobile terminal 600 and the in-vehicle device 610 are connected via short-range wireless communication such as Bluetooth®. Furthermore, the evaluation acquisition unit 190 may transmit parameter information to the in-vehicle device 610 in response to user instructions via the input unit 180. The evaluation acquisition unit 190 may cause the in-vehicle device 610 to set the parameter information by transmitting the parameter information to the in-vehicle device 610.

[0080] The in-vehicle device 610 includes a third information acquisition unit 627, a third mask generation unit 160, and an in-vehicle output unit 630. The third information acquisition unit 627 acquires third vehicle information that indicates the actual operating state of the target vehicle. The third information acquisition unit 627 may acquire actual CAN data in real time during the actual operation of the target vehicle as third vehicle information.

[0081] The third mask generation unit 160 has the same configuration as the second mask generation unit 160 in the first configuration example and may operate in the same manner. The third mask generation unit 160 is connected to the evaluation acquisition unit 190. The third mask generation unit 160 sets the parameter information received from the evaluation acquisition unit 190 as parameter information for the second noise mask of the target vehicle. The third mask generation unit 160 generates the second noise mask according to the third vehicle information acquired by the third information acquisition unit 627 and the set parameter information. The third mask generation unit 160 may receive CAN data from the actual operation of the target vehicle as third vehicle information in real time and generate the second noise mask according to the CAN data and parameter information. The third mask generation unit 160 may not generate the first noise mask for evaluation. In addition, the second mask generation unit 620 in this configuration example generates the first noise mask for evaluation but may not generate the second noise mask during the actual operation of the vehicle. In other words, the third mask generation unit 160 in the second configuration example may be the same as the second mask generation unit 160 in the first configuration example in terms of its function of generating a second noise mask during the actual operation of the vehicle.

[0082] The on-board output unit 630 is connected to the third mask generation unit 160. The on-board output unit 630 may amplify the second noise mask generated by the third mask generation unit 160 using an amplifier or the like and output it to the vehicle speaker 40. The vehicle speaker 40 may be a speaker mounted on the target vehicle and will sound the second noise mask.

[0083] In the second configuration example system 10, the user can efficiently audition and evaluate the noise mask using the mobile terminal 600. Furthermore, if the target vehicle is a vehicle shared by multiple users, such as a rental car, the evaluated parameter information can be supplied to the in-vehicle device 610 when a user gets into the vehicle, allowing the vehicle to output different noise masks for each user.

[0084] Figure 7 shows an example of a symbol list 700 used in the vehicle-side device 30 for evaluating the first noise mask. The symbol list 700 may be a table showing the correspondence between symbols and parameter information. The symbol list 700 includes symbol 1 corresponding to parameter information 1 of the first noise mask 1, symbol 2 corresponding to parameter information 2 of the first noise mask 2, and symbol 3 corresponding to parameter information 3 of the first noise mask 3. The symbol list 700 may store the contents of the parameter information and may also store data representing the symbols. Each symbol may be a name or image, etc., representing the corresponding first noise mask, and may be displayed on a display device for presentation to the user.

[0085] The evaluation acquisition unit 190 may store multiple parameter information acquired by the second information acquisition unit 150 in its storage unit. The evaluation acquisition unit 190 may set symbols for each of the multiple first noise masks corresponding to each of the multiple parameter information, and generate a symbol list 700 containing the set symbols. In S270, the evaluation acquisition unit 190 may receive a selection of one symbol from the symbol list 700 from the user via the input unit 180, and cause the second mask generation unit 160 to set the parameter information corresponding to the selected symbol.

[0086] The evaluation unit 190 may receive new parameter information from the server 20 that satisfies a predetermined degree of approximation to the feature quantities of the first noise mask associated with the parameter information corresponding to the evaluation information, and that is different from the parameter information stored in the evaluation unit 190, and update the symbol list 700 based on the newly received parameter information and the parameter information already stored. The evaluation unit 190 may update the symbol list 700 in S280 with the parameter information of the first noise mask re-selected by the server 20. The evaluation unit 190 may update the symbol list 700 by deleting parameter information 1-3 in the symbol list 700 and setting the newly received parameter information in the symbol list 700. The vehicle-side device 30 may execute S250-S270 using the parameter information included in the updated symbol list 700.

[0087] Figure 8 shows an example of an input reception screen 800 used for evaluating a second noise mask in the vehicle-side device 30. The input reception screen 800 displays multiple symbols in the symbol list 700. The input unit 180 may display the input reception screen 800 on the display screen of the vehicle-side device 30 and receive a symbol selection from the user to obtain evaluation information regarding the first noise mask corresponding to the selected symbol. For example, the user may select the symbol corresponding to their favorite first noise mask from among multiple first noise masks on the input reception screen 800. The input reception screen 800 may also be used for the user's selection of the next first noise mask to be played in the evaluation. In this case, the vehicle-side device 30 may play the first noise mask according to the user's selection on the input reception screen 800.

[0088] Various embodiments of the present invention may be described with reference to flowcharts and block diagrams, where a block may represent (1) a stage in a process in which an operation is performed or (2) a section of a device having the role of performing the operation. Specific stages and sections may be implemented by dedicated circuits, programmable circuits supplied with computer-readable instructions stored on a computer-readable medium, and / or processors supplied with computer-readable instructions stored on a computer-readable medium. Dedicated circuits may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuits may include reconfigurable hardware circuits, including logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logic operations, flip-flops, registers, memory elements such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), etc.

[0089] Computer-readable media may include any tangible device capable of storing instructions to be executed by a suitable device, and as a result, computer-readable media having instructions stored therein will comprise a product containing instructions that can be executed to create means for performing operations specified in a flowchart or block diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disk read-only memory (CD-ROM), digital multipurpose disc (DVD), Blu-ray® disc, memory stick, integrated circuit card, etc.

[0090] Computer-readable instructions may include assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, Java®, C++, and traditional procedural programming languages ​​such as the C programming language or similar programming languages.

[0091] Computer-readable instructions may be provided locally or via a wide area network (WAN) such as a local area network (LAN) or the internet to the processor or programmable circuit of a programmable data processing device such as a general-purpose computer, a special-purpose computer, or another computer, and the computer-readable instructions may be executed to create means for performing operations specified in a flowchart or block diagram. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0092] Figure 9 shows an example of a computer 2200 in which multiple aspects of the present invention may be embodied in whole or in part. A program installed on the computer 2200 can cause the computer 2200 to function as an operation or one or more sections of an apparatus according to an embodiment of the present invention, or to execute such operation or one or more sections, and / or to cause the computer 2200 to execute a process or a stage of such process according to an embodiment of the present invention. Such a program may be executed by the CPU 2212 to cause the computer 2200 to perform a particular operation associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0093] The computer 2200 according to this embodiment includes a CPU 2212, RAM 2214, a graphics controller 2216, and a display device 2218, which are interconnected by a host controller 2210. The computer 2200 also includes input / output units such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes legacy input / output units such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0094] The CPU 2212 operates according to programs stored in the ROM 2230 and RAM 2214, thereby controlling each unit. The graphics controller 2216 retrieves image data generated by the CPU 2212 from a frame buffer provided in RAM 2214 or from itself, and displays the image data on the display device 2218.

[0095] The communication interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads programs or data from the DVD-ROM 2201 and provides them to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from the IC card and / or writes programs and data to the IC card.

[0096] The ROM 2230 stores boot programs and / or programs that depend on the computer 2200's hardware, which are executed by the computer 2200 when activated. The input / output chip 2240 may also connect various input / output units to the input / output controller 2220 via parallel ports, serial ports, keyboard ports, mouse ports, etc.

[0097] The program is provided on a computer-readable medium such as a DVD-ROM 2201 or an IC card. The program is read from the computer-readable medium and installed on a hard disk drive 2224, RAM 2214, or ROM 2230, which are also examples of computer-readable medium, and executed by the CPU 2212. The information processing described within these programs is read by the computer 2200, resulting in coordination between the program and the various types of hardware resources described above. The apparatus or method may be configured to realize the manipulation or processing of information in accordance with the use of the computer 2200.

[0098] For example, when communication is performed between a computer 2200 and an external device, the CPU 2212 may execute a communication program loaded into RAM 2214 and, based on the processing described in the communication program, instruct the communication interface 2222 to perform communication processing. Under the control of the CPU 2212, the communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in a recording medium such as RAM 2214, a hard disk drive 2224, a DVD-ROM 2201, or an IC card, transmits the read transmission data to the network, or writes received data received from the network to a reception buffer processing area provided on the recording medium.

[0099] Furthermore, the CPU 2212 may read all or necessary parts of files or databases stored on external storage media such as the hard disk drive 2224, DVD-ROM drive 2226 (DVD-ROM 2201), or IC card into the RAM 2214, and perform various types of processing on the data in the RAM 2214. The CPU 2212 then writes the processed data back to the external storage media.

[0100] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and subjected to information processing. The CPU 2212 may perform various types of processing on the data read from RAM 2214, including various types of operations, information processing, conditional judgments, conditional branching, unconditional branching, information retrieval / replacement, etc., as described throughout this disclosure and specified by the program instruction sequence, and write the results back to RAM 2214. The CPU 2212 may also retrieve information in files, databases, etc., within the recording medium. For example, if multiple entries are stored in the recording medium, each having an attribute value of a first attribute associated with an attribute value of a second attribute, the CPU 2212 may search among the multiple entries for an entry that matches the condition for which the attribute value of the first attribute is specified, read the attribute value of the second attribute stored in that entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0101] The programs or software modules described above may be stored on or near computer 2200 on a computer-readable medium. Alternatively, recording media such as hard disks or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as computer-readable media, thereby providing programs to computer 2200 via the network.

[0102] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications or improvements can be made to the above embodiments. It will be clear from the claims that such modified or improved forms may also be included in the technical scope of the present invention.

[0103] It should be noted that the execution order of operations, procedures, steps, and stages in the apparatus, systems, programs, and methods shown in the claims, specifications, and drawings is not explicitly stated as "before," "prior to," etc., and that these can be implemented in any order unless the output of a previous process is used in a later process. Even if the operation flow in the claims, specifications, and drawings is described using phrases such as "first," "next," etc. for convenience, it does not mean that it is essential to perform the operations in that order. [Explanation of Symbols]

[0104] 1. Source Sound Unit 2. Source Sound Unit 3. First Noise Mask 10 Systems 20 servers 30 Vehicle-side equipment 40 vehicle speakers 100 1st Information Acquisition Department 110 Decision Section 120 Evaluation Mask Supply Unit 122 First Mask Generation Unit 124 Cluster Unit 126 Selection Section 130 First Communications Department 140 Second Communications Department 150 2nd Information Acquisition Department 160 Second Mask Generation Unit 160 Third Mask Generation Unit 170 Output section 180 Input section 190 Evaluation Acquisition Department 300 Acoustic Model Section 310 Volume adjustment section 400 Source Audio Section 410 Pitch bend loop section 420 Volume adjustment section 430 Addition section 600 mobile devices 610 On-vehicle equipment 620 Second Mask Generation Unit 625 Terminal Speaker 627 Third Information Acquisition Department 630 In-vehicle output unit 700 Symbol List 800 Input Acceptance Screen 2200 Computers 2201 DVD-ROM 2210 Host Controller 2212 CPU 2214 RAM 2216 Graphics Controller 2218 Display Devices 2220 Input / Output Controller 2222 Communication Interface 2224 Hard Disk Drive 2226 DVD-ROM drive 2230 ROM 2240 Input / Output Chip 2242 keyboard

Claims

1. A system comprising a server and vehicle-side equipment, A determination unit that determines the expected characteristic quantities of the expected noise based on vehicle information, Based on the assumed feature quantities, an evaluation mask supply unit supplies at least one first noise mask for evaluation, An evaluation unit that acquires user evaluations for each of the first noise masks used for evaluation, The system includes a second mask generation unit that generates a second noise mask to be used during actual vehicle operation, in accordance with the user evaluation. The evaluation mask supply unit is, A first mask generation unit that generates a plurality of the first noise masks, A clustering unit that determines the feature quantities of each of the plurality of first noise masks and clusters them into a plurality of clusters based on the respective feature quantities, The system includes a selection unit that selects at least one first noise mask for evaluation from the clusters corresponding to the assumed feature quantities among the plurality of clusters. system.

2. The evaluation mask supply unit is, A first noise mask is obtained that satisfies a predetermined similarity condition with respect to the aforementioned assumed feature quantities. Identify the cluster containing the acquired first noise mask from the plurality of clusters. The system according to claim 1.

3. The assumed features are extracted based on the spectrum of the transition frequency region in which the assumed noise peak frequency transitions. The system according to claim 2.

4. The evaluation mask supply unit supplies a plurality of the first noise masks, each differing in aspects other than the assumed feature quantities. The system according to claim 2.

5. The volume of the second noise mask is greater than the volume of the assumed noise. The system according to claim 1.

6. The evaluation unit acquires the user evaluation by simultaneously reproducing the assumed noise and the first noise mask for evaluation. The system according to claim 1.

7. The database contains records of the aforementioned assumed noise levels. The system according to claim 1.

8. The vehicle-side device comprises the evaluation acquisition unit and the second mask generation unit, The vehicle-side device acquires the parameter information of the first noise mask for evaluation that has been transmitted from the server to the vehicle-side device. The system according to claim 1.

9. The vehicle-side device includes an in-vehicle device and a mobile terminal. The mobile terminal wirelessly transmits the parameter information to the server. The system according to claim 8.

10. The parameter information of the first noise mask for evaluation includes waveform information that defines at least one of the frequency components and amplitude of the first noise mask for evaluation. The system according to claim 8.

11. A method performed by a system comprising a server and vehicle-side equipment, Based on vehicle information, the expected noise characteristics are determined, Based on the aforementioned assumed features, at least one first noise mask for evaluation is supplied, Obtain user evaluations for each of the first noise masks used for evaluation, The system also includes generating a second noise mask to be used during actual vehicle operation, in accordance with the user evaluation. Supplying the first noise mask for the aforementioned evaluation means To generate a plurality of the first noise masks, The characteristic quantities of each of the aforementioned multiple first noise masks are determined, and the masks are clustered into multiple clusters based on the respective characteristic quantities. This includes selecting at least one first noise mask for evaluation from the clusters corresponding to the assumed features among the plurality of clusters. method.

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