39 results about "Psychoacoustics" patented technology

The invention discloses a college dormitory noise multi-dimensional evaluation method based on psychoacoustic and sound field simulation, and belongs to the field of building environment and noise control. The objective of the invention is to solve the problem that an existing dormitory noise evaluation method is single in index and neglects subjective perception and spatial distribution heterogeneity. The method comprises the following steps: acquiring physical data and original audio of dormitory noise through multi-point synchronous acquisition; calculating loudness, sharpness, roughness, fluctuation intensity and comprehensive psychoacoustic annoyance (PA) by using a psychoacoustic model, and scientifically quantifying subjective interference of noise; meanwhile, sound field simulation is carried out based on the accurately established three-dimensional dormitory model, a sound pressure level distribution cloud picture is generated, and a standing wave phenomenon and a sound energy accumulation area are visually revealed; and finally, generating a targeted noise reduction optimization strategy by integrating subjective and objective and spatial analysis results. According to the method, full-chain diagnosis of physical characteristics-subjective perception-spatial distribution of dormitory noise is realized, and a scientific basis is provided for accurate and efficient noise treatment.

The invention relates to the technical field of audio signal processing, and discloses a wind-noise-resistant self-adaptive volume adjustment method and system for a riding earphone, and the method comprises the following steps: S1, collecting environment sound and a source audio signal in parallel; s2, analyzing environment sound, and determining macroscopic adjustment intensity; s3, analyzing the source audio in parallel, and identifying a content type and a transient signal of the source audio; s4, based on the psychological acoustic model, generating a frequency-related target method tone quality compensation gain; s5, performing dynamic smoothing and frequency weighting on the target gain according to the content and the transient characteristics to generate an application gain; s6, fusing the macroscopic adjustment intensity and the application gain, and synthesizing a final gain parameter; and S7, applying the final gain to the source audio, and outputting the compensated audio. According to the method, the psychological acoustic model and audio content parallel analysis are fused, frequency-level accurate compensation is realized, the problems of traditional degradation and sudden hearing sense change are solved, and the audio definition and comfort are improved.

The application relates to the technical field of audio processing, in particular to an audio processing method, an electronic device and a readable storage medium. In the method, a sound signal is received by a device that can be worn on the ear of a user, then the sound signal is divided into a low-frequency sound signal and a high-frequency sound signal by using a filter, and a steady-state sound signal and a transient sound signal in the low-frequency sound signal and the high-frequency sound signal are extracted. The steady-state sound signal and the transient sound signal are processed based on the individual calibration parameters corresponding to the user, so that the calibrated sound signal finally heard by the user conforms to the target psychoacoustic loudness of the user. In this way, the hearing protection of the user can be realized.

The application provides a noise annoyance modeling method for an audio injection system, which comprises the following steps: firstly, according to a target sound, a corresponding control sound is selected to perform time domain superposition, so as to obtain a plurality of superimposed sound samples; then, a subjective evaluation experiment and data processing are performed on the obtained superimposed sound samples; then, psychoacoustic parameters of the target sound, the control sound and the superimposed sound are calculated, and the difference between the corresponding psychoacoustic parameters of the target sound and the control sound is calculated; the difference between the calculated psychoacoustic parameters of the target sound and the control sound is taken as an independent variable, and the corresponding superimposed sound annoyance score value is taken as a dependent variable; the correlation between the independent variable and the dependent variable, the correlation between the independent variables and the collinearity between the independent variables are calculated; according to the calculation results, the modeling independent variable is determined; the determined modeling independent variable and the superimposed sound annoyance score value are taken as the dependent variable, and a multiple linear regression is adopted to realize the audio injection superimposed sound annoyance modeling. The application improves the precision and parameter correlation of the model, and further improves the objective evaluation of the audio injection superimposed sound annoyance.

The invention discloses an audio watermark generation and detection method. The method comprises the following steps: acquiring an audio signal corresponding to an audio to be processed; the amplitude of the confrontation disturbance signal is smaller than that of a value set corresponding to a psychological acoustic masking threshold value of the audio signal, the psychological acoustic masking threshold value is used for quantitatively representing an added disturbance amplitude upper limit corresponding to each frequency point in the audio signal, and the confrontation disturbance signal is used for carrying watermark information of the audio to be processed; and embedding the adversarial disturbance signal into the audio signal. The technical problem that the audio watermarking technology adopted in the related technology is mostly based on a static or dominant embedding mode and is easily removed by an attacker through a signal processing method is solved.

The invention relates to the technical field of sound field control, in particular to a sound equipment sound field low-frequency increasing and decreasing method and system based on volume amplitude recognition, and the method comprises the following steps: collecting an original audio stream, and extracting instantaneous amplitude features; calculating a low-frequency compensation coefficient according to the nonlinear auditory model; constructing a dynamic safety threshold and correcting a coefficient in combination with the physical limit of the equipment; and adjusting the low-frequency component based on the corrected parameter, and generating an optimized sound field signal. According to the invention, by establishing a dynamic mapping and constraint mechanism between the instantaneous volume amplitude and the low-frequency gain, the technical defects that the low-frequency hearing feeling of a traditional sound system is deficient under the low volume and overload distortion is extremely easy to occur under the high volume are thoroughly solved, and under the premise of strictly guaranteeing the physical safe operation of loudspeaker hardware, the sound quality is greatly improved. And full-dynamic-range sound field adaptive equalization and restoration conforming to human ear psychological acoustic characteristics are realized.

The invention discloses a distributed snore monitoring and shielding system cooperating with a charging box, and belongs to the technical field of audio signal processing and active noise reduction, the system comprises a charging box unit and an earphone unit, the charging box unit collects indoor sound field information through a microphone array, snore detection and feature analysis are carried out by using a neural network, and the earphone unit is connected with the charging box unit; distinguishing snore sources through a snore fingerprint recognition algorithm; the earphone unit generates counteracting sound waves and shielding audios according to snore feature data, accurate shielding is achieved through a mixed noise reduction strategy combining active noise reduction and psychological acoustic shielding, the system can recognize six typical snore modes, the detection rate reaches 97.3%, the shielding effective rate reaches 92.1%, power consumption is reduced by 45% compared with a traditional scheme, and a quiet and comfortable sleep environment is provided for a user.

The invention relates to the technical field of vehicle sound quality, in particular to a vehicle lifting beacon sound quality optimization method and device, and the method comprises the steps: collecting the noise of a plurality of types of corresponding lifting beacons of a plurality of vehicles in the lifting process, and carrying out the analysis to obtain a plurality of psychological acoustic parameters in the lifting process; obtaining a noise subjective score of the rising and falling vertical mark; and analyzing relevancy between the psychoacoustic parameters and the noise subjective score to determine at least one objective evaluation item of the rising and falling standard and a corresponding objective parameter index according to the relevancy so as to optimize an actual index of the at least one objective evaluation item of the rising and falling standard until the objective parameter index corresponding to the at least one objective evaluation item is reached. Therefore, the problems that in the prior art, the engine noise and the NVH noise of the vehicle are optimized by independently depending on the noise reduction sound pressure level, a special evaluation method for the special acoustic characteristics of the lifting beacon is lacked, and the use requirement and the optimization requirement of actual engineering cannot be met are solved.

The invention relates to the technical field of vehicle sound quality, in particular to a hidden outer handle sound quality optimization method and device, and the method comprises the steps: collecting the noise of a hidden outer handle of a vehicle in the opening and closing process, so as to analyze a plurality of psychological acoustic parameters in the opening and closing process; obtaining a noise subjective score of the hidden outer handle; and analyzing relevancy between the psychoacoustic parameters and the noise subjective score to determine at least one objective evaluation item of the hidden outer handle and a corresponding objective parameter index so as to optimize the hidden outer handle until the actual index reaches the objective parameter index corresponding to the at least one objective evaluation item. Therefore, the problems that in the prior art, the noise of the vehicle and the outer handle of the vehicle door is optimized by independently depending on the sound pressure level for reducing the noise, it is difficult to effectively connect with the actual subjective feeling of a user on the noise, targeted optimization cannot be conducted, and the use requirements of a driver and passengers and the optimization requirements in an actual scene cannot be met are solved.

This invention discloses a method for detecting frequency shift and abnormal noise in pedestrian warning devices for electric vehicles. The method triggers audio by sending a simulated operating condition message and eliminates time delay errors by synchronizing with the underlying hardware clock. The acquired audio is sequentially filtered and scaled, and effective signal segments are extracted using short-time energy and zero-crossing rate. After phase-aligned splitting, the psychoacoustic features, harmonic distortion, and frequency shift response parameters of each subsequence are extracted. Finally, a feature local distance matrix is ​​constructed, and a dynamic programming algorithm is used to calculate the minimum cumulative cost path to output the sound defect type, while simultaneously verifying the linear mapping relationship between frequency shift response and vehicle speed. This invention effectively eliminates time delay and noise interference, achieving high-precision automatic classification of abnormal noise and accurate verification of frequency shift characteristics.

The invention discloses an automobile sound effect intelligent evaluation system and method based on deep learning, and relates to the field of automobile engineering and artificial intelligence, and the system comprises an audio data collection module, a psychoacoustic feature extraction module, a deep learning evaluation module and an optimization guidance module. The system obtains an original audio signal of a vehicle, extracts psychoacoustic parameters such as loudness and sharpness, and constructs a time sequence feature matrix; performing convolution operation and nonlinear mapping on the feature matrix by using a pre-trained one-dimensional convolutional neural network model, and outputting predicted values of subjective evaluation indexes such as fluency, comfort and luxury; and key parameters influencing the sound quality are identified by calculating the gradient of the predicted value relative to the input matrix. According to the method, automatic objective evaluation of the automobile sound effect is realized, a mapping relation between physical parameters and subjective hearing is established, optimization guidance based on attribution analysis can be provided, and the adaptability of an evaluation model to a dynamic driving scene is ensured.

The application discloses a rail transit wall-attached sound-absorbing layer structure and a design method thereof. The sound-absorbing layer structure is composed of three layers of curlable sound-absorbing materials, and is respectively a noise capturing layer, an acoustic corridor layer and a low-frequency suppression layer along the radial direction of a tunnel. A plurality of regular hexagonal micro-porous channel units are arranged in an array on the noise capturing layer. The acoustic corridor layer is provided with staggered cavity corridor structures in an array, so that sound waves are reflected multiple times to convert sound energy into internal energy. The low-frequency suppression layer is provided with arrayed mass concentration units. Due to the difference in density between the arrayed mass concentration units and the film, the vibration of the system composed of the arrayed mass concentration units and the film is opposite, so that the sound-absorbing performance of the whole material is improved. According to the psychoacoustic annoyance degree, the sound-absorbing layer structure can be optimized, so that the design of the sound-absorbing layer structure meets the comfort of drivers and passengers during train driving, prevents work errors of train staff due to hearing insensitivity, and guarantees safe operation of the train.

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.

The invention discloses a self-adaptive audio signal processing method and system for suppressing physical displacement of a Bluetooth sound box. The method monitors system volume gain in real time, and triggers control logic when it exceeds a displacement critical threshold calibrated by hardware coherence parameters. The system utilizes a band-pass filter to separate a target frequency band component corresponding to the physical resonance frequency of the box body, performs energy time domain integration on the component in a time sliding window, and calculates a displacement potential energy accumulation value. And when the accumulated value exceeds a static friction force breakthrough threshold value combined with the voice coil heat accumulation model, generating a dynamic attenuation coefficient to perform smooth suppression on the amplitude of the frequency band. According to the invention, machine-by-machine calibration is carried out on algorithm parameters by using loudspeaker impedance and inductance data actually measured by a precise LCR digital bridge in a production stage, and the suppressed low-frequency hearing feeling is compensated through higher harmonics in combination with a psychoacoustic principle, so that the problem of automatic sliding of the lightweight portable sound box during large dynamic playing is effectively solved.

The invention relates to the technical field of psychoacoustic and electroacoustic measurement, and provides an equal-loudness-level curve calculation method suitable for a plug-in headphone, and the method comprises the steps: firstly, calculating a free field equal-loudness-level curve based on a standard, and deducing an increment function representing a human ear loudness perception growth rate; then, acquiring a pure tone reference equivalent threshold sound pressure level of the plug-in earphone in a blocked ear environment, and realizing full-frequency-point reference data fitting by using an interpolation algorithm; and finally, superposing the loudness increment function on the reference equivalent threshold sound pressure level reference anchor point, thereby constructing an equal loudness level curve suitable for the plug-in earphone. The technical blank that the plug-in earphone lacks an equal-loudness evaluation standard in a blocked ear scene is solved, and an important support and an application basis are provided for application expansion of an equal-loudness-level curve relation.

The invention discloses an emergency broadcasting method, a terminal and a storage medium. The method comprises the following steps: receiving an environment audio and video stream; separating human voice and environment voice categories based on the prompt vector; performing audio-visual cooperative positioning based on human voice, and extracting a face image; performing anti-shielding tracking on the target, and outputting continuous coordinates; human voice and human face features are fused to analyze emotion, and a panic index is output; in combination with the coordinates, the panic index and the environmental sound category, generating a safety guidance instruction through neural symbol reasoning; generating voice according to the instruction and performing psychoacoustic modulation based on the panic index; and finally generating beam forming parameters based on the coordinates. According to the method, the technical problem that the traditional broadcast cannot generate and precisely project the voice instruction with the psychological pacifying effect according to the specific position and the real-time psychological state of the target in a complex disaster site is solved.

The invention is suitable for the technical field of audio signal processing, and provides a sparse auditory pulse coding method and device fusing a masking effect and a dynamic threshold. According to the auditory rarefaction method provided by the embodiment of the invention, a human auditory perception mechanism can be combined, and the threshold group characteristics are utilized to realize time sequence pulse coding, so that the audio signal can directly adapt to the pulse neural network model, the coding efficiency and fidelity are improved, and meanwhile, the data redundancy is reduced. While the perception quality is ensured, the number of pulse events can be remarkably reduced, the energy efficiency and accuracy of a recognition task are improved, and the method is naturally adaptive to brain-like hardware and a pulse neural network. According to the embodiment of the invention, the masking effect of psychoacoustics is fused into the pulse coding process for the first time, and is highly consistent with the feeling and processing mode of organisms on sound signals. The biological reasonability is relatively high.

The application provides an audio signal processing method, device and storage medium. The method constructs a dynamic loudspeaker model through a key mechanical parameter obtained in real time, constructs a listening area sound pressure mapping according to a listening position transfer function of the loudspeaker, a listening area parameter and the dynamic loudspeaker model, inputs the listening area sound pressure mapping and low-frequency digital signals in an original audio digital signal to be played into a psychoacoustic model, performs masking filtering on the low-frequency digital signals based on a masking spectrum obtained, thereby performing filtering processing on audio in the audio digital signals that cannot be perceived by a user, and reduces the power of the loudspeaker under the premise of ensuring sound quality, and improves user experience.

This invention discloses a sound quality modeling method for air conditioners, comprising: acquiring sound signals from the air conditioner; objectively analyzing the acquired sound signals to obtain psychoacoustic parameters; subjectively evaluating the acquired sound signals to obtain subjective evaluation results; establishing a non-equal loudness sound quality model based on the psychoacoustic parameters and the subjective evaluation results; processing multiple sound signals to equal loudness to obtain equal loudness sound signals; objectively analyzing the equal loudness sound signals to obtain equal loudness psychoacoustic parameters; subjectively evaluating the equal loudness sound signals to obtain equal loudness subjective evaluation results; establishing an equal loudness sound quality model based on the equal loudness psychoacoustic parameters and the equal loudness subjective evaluation results; and establishing a comprehensive sound quality model using the equal loudness sound quality model and the non-equal loudness sound quality model. This invention proposes a sound quality modeling method for air conditioners, and the established sound quality model has high accuracy in sound quality prediction.

The present disclosure relates to an audio processing method and device, electronic equipment and storage medium. The method comprises: determining a first audio signal from an initial audio based on a signal value of an audio signal in the initial audio; reducing a signal value of a second audio signal adjacent to the first audio signal to obtain an output audio signal; wherein the first audio signal and the second audio signal produce a masking effect; and obtaining a to-be-played audio based on the output audio signal. By reducing the second audio signal adjacent to the first audio signal to the output audio signal, the influence of the masking effect can be reduced, hearing protection is achieved by using the masking effect in psychoacoustics, the objective output energy of the sound is effectively reduced, the sound radiation of the music playing device to the human ear is reduced, and the perception of the human ear to the sound volume reduction is not caused, that is, the subjective listening experience is unchanged; and no frequency band processing is required, and the computing power requirement is reduced.

The invention provides a real-time speech enhancement method and system based on an adaptive deep neural network, and belongs to the technical field of speech signal processing. The method comprises the following steps: collecting multiple paths of voice signals through a multi-microphone array, and suppressing environmental noise by using a beam forming algorithm; processing the voice signal by adopting a hybrid noise reduction method of wavelet transform and adaptive filtering; constructing a dynamic neural network model, dynamically adjusting the network weight according to the noise environment classification result, and enhancing the voice signal; frequency band energy compensation is carried out on the enhanced voice in combination with a psychological acoustic model, and auditory fatigue is reduced; and finally, reconstructing a time domain voice signal through inverse short-time Fourier transform, and carrying out post-processing to output a final enhanced voice. The method has the advantages of being high in adaptability, high in real-time performance, good in voice quality and the like, and is suitable for various scenes such as voice communication, voice recognition, intelligent voice assistants and the like.

A system provides for psychoacoustic frequency range extension. The system generates quadrature components from an audio channel, and generates rotated spectral quadrature components by applying a forward transformation that rotates a spectrum of the quadrature components from a standard basis to a rotated basis. In the rotated basis, the system isolates components of the rotated spectral quadrature components at target frequencies, and generates weighted phase-coherent harmonic spectral quadrature components by applying a nonlinearity to the isolated components having a dependence on scale that is subject to constraints. The circuitry generates a harmonic spectral component by applying an inverse transformation that rotates a spectrum of the weighted phase-coherent harmonic spectral quadrature components from the rotated basis to the standard basis. The circuitry combines the harmonic spectral component with frequencies of the audio channel outside of the target frequencies to generate an output channel, and provides the output channel to a speaker.

This invention provides a method and system for training an artificial neural network model to extract features indicating variations in psychoacoustic attributes from digital audio signals and generate contextual latent spatial representations. [Solution] The learning system consists of a read / decode logic that reads a specific digital audio signal source from a set of digital audio signal sources associated with a specific sound content category, a transform logic that generates a time-frequency representation based on the specific digital audio signal, and a learning logic that uses an artificial neural network to learn a set of numerical codes that provide a latent spatial representation of the time-frequency representation. The read, generate, and learn process is repeated to train the artificial neural network. The model database retrieves a set of model parameters learned from the trained artificial neural network and stores them in a computer storage medium.

A signal-processing method has the steps of: obtaining a plurality of signal components from an input signal, the plurality of signal components including a plurality of perceptual feature components, and further including a first-directional signal component, a second-directional signal component, a non-directional signal component, or a combination thereof; using at least a pair of filters to filter each of the plurality of signal components into a filtered first-directional signal and a filtered second-directional signal, thereby forming a group of filtered first-directional signals and a group of filtered second-directional signals; and obtaining a first output signal and a second output signal for outputting and / or analysis, the first output signal including a combination of the group of filtered first-directional signals, and the second output signal including a combination of the group of filtered second-directional signals.

This invention belongs to the field of noise control and acoustic design of rail transit vehicles, and discloses a forward design method for low-noise interior of a power-centralized EMU combined with sound quality optimization. The steps are as follows: First, determine the design target value for the in-vehicle noise sound pressure level and the target value for the comprehensive annoyance index of sound quality. Second, based on the whole-vehicle noise simulation model, allocate noise limits from the perspective of sound source-transmission path combinations, and verify the rationality of the allocation results in conjunction with engineering feasibility requirements. Third, establish independent simulation models for different sound source-transmission path combinations, determine initial optimization design parameters, and input them into the whole-vehicle noise simulation model for iterative optimization to ensure that the total A-weighted sound pressure level in the passenger compartment reaches the design target. After the sound pressure level meets the target, obtain the comprehensive annoyance index of sound quality using a sound quality evaluation and prediction model. When the sound quality does not meet the target, locate the psychoacoustic parameters affecting the sound quality and the corresponding sound source-transmission path combinations, and perform secondary optimization until the sound quality meets the target.

The invention is suitable for the technical field of audio data processing, provides a wireless microphone audio processing method and a related device, and realizes lower delay, high stability and sound quality output acceptable to human ears for audio signals. The method is applied to a wireless audio processing system comprising a wireless microphone and wireless receiving equipment, and comprises the following steps: the wireless microphone performs feature extraction of self-adaptive dynamic framing on an original audio signal, performs weight adjustment according to a preset psychological acoustic model, and adopts finite scalar quantization mapping to obtain discrete symbols; performing context sensing entropy coding according to the characteristic sequence dependency relationship of each audio symbol in the discrete audio symbol set to obtain an audio coding stream, and transmitting the audio coding stream to wireless receiving equipment; and the wireless receiving equipment decodes and complements the audio coding stream, and synthesizes a target audio feature according to the scalar value of the complemented discrete audio symbol set and the adjusted audio weight value.

The present application relates to the technical field of audio signal processing, and discloses an anti-wind-noise adaptive volume adjustment method and system for a riding earphone, the method comprising the following steps: S1, collecting ambient sound and source audio signals in parallel; S2, analyzing the ambient sound to determine a macro adjustment intensity; S3, analyzing the source audio in parallel to identify its content type and transient signals; S4, generating frequency-dependent target method sound quality compensation gain based on a psychoacoustic model; S5, dynamically smoothing and frequency-weighting the target gain according to the content and transient characteristics to generate an application gain; S6, fusing the macro adjustment intensity and the application gain to synthesize a final gain parameter; and S7, applying the final gain to the source audio to output the compensated audio. The present application fuses psychoacoustic model and parallel analysis of audio content, realizes frequency-level accurate compensation, solves the problems of traditional degradation and sudden changes in listening experience, and improves audio clarity and comfort.

A quantized audio signal is received. A decoder generates, based on the quantized audio signal and using a first dequantization operation, at least one local maximum discrete cosine transform (DCT) coefficient. The decoder determines at least one masking function based on the at least one DCT coefficient and generates a set of modified quantized values based on applying the at least one masking function to a set of quantized values of the quantized audio signal. The decoder generates a dequantized audio signal by dequantizing the set of modified quantized values. The decoder generates and outputs a reconstructed audio signal based on the dequantized audio signal.

The invention discloses a self-adaptive sound field control and privacy protection method and system based on semantic driving. The method comprises the following steps: firstly, estimating environment impulse response and inverting equivalent sound velocity in real time through a distributed microphone array, and generating scene semantic features in combination with user identity and position; thirdly, mapping the semantic features into semantic state tags, dynamically adjusting weights and constraint conditions in a model predictive control cost function according to the semantic state tags, and realizing self-adaptive switching of a control strategy among a privacy protection mode, an emergency priority mode and a conventional equilibrium mode; and finally, driving a loudspeaker array based on the solved parameters, performing beam forming on the target area, forming beam null for the adjacent potential eavesdropping area, and directionally playing masking noise based on residual speech spectrum synthesis. Through the closed-loop environment perception and psychoacoustic masking technology, the problems that the open space sound field control strategy is rigid and privacy protection is difficult are solved, and the environment adaptability and safety of the system are improved.

The invention discloses a vehicle-mounted sound system fine calibration method based on a critical frequency band and a stereo imaging sound layer model. The method is based on an innovative'imaging sound layer 'psychological acoustic model, and the core of the method comprises the following steps: collecting a dual-track acoustic response in a vehicle; based on an ERB model, dividing an analysis sub-frequency band corresponding to an imaging sound layer, and identifying a miscoordination target frequency band by calculating an energy difference; and asymmetrically adjusting the parameters of the other sound channel by taking a single sound channel as a fixed reference so as to reduce the deviation. According to the method, an automatic progressive double-ring calibration strategy is preferably adopted, correction is completed in combination with a sine wave probe and a fine step length, and the sound field quality is ensured through objective verification and subjective acceptance. In addition, a parameter prediction model optimization mechanism based on an expert sample library is introduced, so that the system has a continuous optimization capability. According to the method, the calibration process is deeply aligned with the auditory characteristics of human ears, the problem of sound image blurring in the complex acoustic environment of the automobile cabin is effectively solved, and the immersive high-fidelity experience is remarkably improved.