237 results about "Acoustic spectrum" patented technology

A combination equalizer and calibrator circuit assembly includes a calibrator formed of a frequency control circuit, a signal generator, an amplifier circuit connected with a microphone, a compare circuit and a display circuit and connected to the front end of an equalizer set. Calibration is made through the calibrator prior to audio system reproduction, wherein the frequency control circuit provides a reference frequency and different test frequencies for causing the signal generator to generate respective sound signals for output through a speaker; the microphone picks up these sound signals for comparison with respective reference values by the compare circuit; and the display circuit displays the respective comparison results. By means of adjustment through respective adjust circuits, signals of test frequencies are standardized so that the music played through the audio system is well calibrated without sound spectrum distortion due to space or audio system discrepancy.

The sound device includes an audio-information output unit, an analysis unit, an audio-division-spectrum output unit, a noise-division-spectrum output unit and a correction unit. The analysis unit receives audio information from the audio-information output unit, and then outputs sound spectrum information. The noise-division-spectrum output unit outputs sound-volume information for each critical band width of a noise, and the audio-division-spectrum output unit outputs the sound-volume information for each critical band width of the sound-spectrum information. The correction unit corrects the information from the audio-division-spectrum output unit based on the information from the noise-division-spectrum output unit. The audio-signal properties can be well corrected corresponding to the auditory-sense properties of the human, and thus the audio sound, in which an uncomfortable feeling to the auditory sense of the human has been adequately controlled, can be transmitted to a user.

A method for detecting and identifying a type and geometric dimensions of hydrocarbon deposits and other underground fluid deposits. Sensors are used to measure anomalies caused by a deposit in a natural earth frequency spectrum. Different frequencies are filtered out and analyzed, for respective deposits. Amplitudes of maxima are separately evaluated, corresponding to separately measured frequencies. Amplitude values of the maxima are placed into correlation with each other and measuring points are determined.

The invention discloses an electronic music-based system and method for precisely judging instrument performance level. Note information of the electronic music is extracted and converted; and then the information and a player performance effect are compared precisely for judgement. During playing, a real-time and precise judgement result can be displayed; and after playing, the playing performance is scored. The system mainly comprises a storage device (10), an electronic music format parsing system (11), a note information recombination and acoustic spectrum calculation system (12), a master control system (13), an accompany output system (14), a music composing display system (15), a music playing analyzing and judging system (16), an audio acquisition system (17), a score calculation system (18), a matching entertainment system (19), a display screen (20), a digital musical instrument acquisition line (21), and a high-definition MIC (22). According to the invention, because of the realized judgement precision, the system and method can be widely applied to professional musical instrument teaching; and learners can be helped, thereby improving the learning efficiency and the playing enjoyment.

The invention discloses a voice synthesis method which comprises the following steps: converting to-be-processed multilingual texts into corresponding mixed phoneme sets, and coding and mapping to obtain a phoneme mixing sequence by utilizing one-hot; generating a text feature sequence from the phoneme mixing sequence by virtue of an encoder; generating predicted acoustic spectrum features from the text feature sequence by virtue of a decoder; synthesizing a voice waveform from the predicted acoustic spectrum features. The embodiment of the invention further discloses a voice synthesis system.With the adoption of the embodiment of the invention, voices of multiple languages can be synthesized, the error of the synthesized voice is reduced, and resources are saved.

At least one exemplary embodiment is directed to an earpiece that includes a fluid in a reservoir where the composition of the fluid or the pressure of the fluid can be modified to vary the insertion loss value of the earpiece.

A system and method for utilizing electronic tokens to increase broadcasting tokens is disclosed. Electronic tokens comprise encoded data that are embedded within broadcasting content and radiated from broadcast appliances, such as in the inaudible ranges of an acoustic spectrum or in an electromagnetic spectrum. The radiated tokens are then captured by a token capture device (TCD) possessed by a consumer. Upon receipt of the token from the broadcast, the TCD processes the token and becomes of value to the consumer. For example, the token may cause the TCD to light up, indicating that the consumer has won a prize. A TCD having indication of token receipt thereon may then be redeemed by the consumer for a prize, thus generating incentive for viewing the broadcast and using the TCD to capture the tokens embedded therein.

The invention provides an in-depth learning-based partial discharge ultrasonic audio frequency identification method and system. The method comprises the following steps: partial discharge ultrasonic signals of an electric power device are detected, partial discharge ultrasonic audio frequency data is obtained and then converted into a sound spectrogram, a depth convolution nerve network model is built, samples are used for training a network, partial discharge ultrasonic audio frequency data to be diagnosed is input into a trained network, and a partial discharge defect type is output and obtained. According to the in-depth learning-based partial discharge ultrasonic audio frequency identification method and system, the partial discharge ultrasonic audio frequency data is converted into the sound spectrogram, a depth convolution nerve network is used for identifying the sound spectrogram, ultrasonic signals of all kinds of defects in partial discharge can be accurately and effectively identified, and a convenient and reliable diagnosis method is provided for electric power device insulation state assessment.

Accurately quantifying optical absorption coefficient using acoustic spectra of photoacoustic signals. Optical absorption is closely associated with many physiological parameters, such as the concentration and oxygen saturation of hemoglobin, and it can be used to quantify the concentrations of non-fluorescent molecules. A sample is illuminated by, for example, a pulsed laser and following the absorption of optical energy, a photoacoustic pressure is generated via thermo-elastic expansion. The acoustic waves then propagate and are detected by a transducer. The optical absorption coefficient of the sample is quantified from spectra of the measured photoacoustic signals. Factors, such as system bandwidth and acoustic attenuation, may affect the quantification but are canceled by dividing the acoustic spectra measured at multiple optical wavelengths.

The invention discloses a Chinese song emotion classification method based on multi-modal fusion. The Chinese song emotion classification method comprises the steps: firstly obtaining a spectrogram from an audio signal, extracting audio low-level features, and then carrying out the audio feature learning based on an LLD-CRNN model, thereby obtaining the audio features of a Chinese song; for lyricsand comment information, firstly constructing a music emotion dictionary, then constructing emotion vectors based on emotion intensity and part-of-speech on the basis of the dictionary, so that textfeatures of Chinese songs are obtained; and finally, performing multi-modal fusion by using a decision fusion method and a feature fusion method to obtain emotion categories of the Chinese songs. TheChinese song emotion classification method is based on an LLD-CRNN music emotion classification model, and the model uses a spectrogram and audio low-level features as an input sequence. The LLD is concentrated in a time domain or a frequency domain, and for the audio signal with associated change of time and frequency characteristics, the spectrogram is a two-dimensional representation of the audio signal in frequency, and loss of information amount is less, so that information complementation of the LLD and the spectrogram can be realized.

An implantable neural stimulation system, such as a cochlear implant system, utilizes a Distributed Compression Amplitude Mapping (DCAM) system to distribute signal compression between a pre-bandpass linear mapping function, and a post-bandpass compressive mapping function. The pre-bandpass linear mapping function is implemented, in one embodiment, as a traditional fast audio compressor to prevent distortion that might result from a non-linear mapping. The post-bandpass compressive mapping function is implemented, in one embodiment, as a logarithmic transform to reflect natural hearing. As a result of the DCAM processing, the differences in amplitudes of components of the acoustic spectrum are maintained. By maintaining these differences, spectral smearing between channels is reduced and speech clues are preserved.

The invention discloses a noise estimating method, a key optimizing method and a system thereof. The method includes the following steps: an initial noise average value of a sound spectrogram is estimated, and an initial elimination threshold value is determined according to the noise average value; wild value elimination processing is carried out for at least one time, so as to eliminate sound spectrogram data larger than the elimination threshold value; after the wild value elimination processing every time, the noise average value is estimated again, so as to determine the elimination threshold value of the next wild value elimination processing; finally, the noise average value estimated the last time is set as a noise estimating result. In the invention, at least one wild value elimination processing is added in the conventional noise estimation so as to eliminate abnormal values with larger amplitude in an original noise curve, and the noise average value is estimated again after the wild value elimination processing so as to carry out the subsequent calculating process.

The invention relates to an intrinsic safety opto-acoustic spectrum gas monitoring system based on an optical acoustic sensor. The Intrinsic safety opto-acoustic spectrum gas monitoring system comprises a light source device which is connected with a photoacoustic cell device through optical fibers and an optical fiber collimator, and the incident direction of laser emitted from the light source is collinearly aligned with the axle center of the photoacoustic cell device; and phase-shifting erbium-doped grating optical fiber with the 1/4 wavelength of the optical acoustic sensor is annularly paved on the inner wall of the photoacoustic cell device, the photoacoustic cell device is communicated with a gas to be tested, and the grating optical fiber is connected with a demodulation device and a data acquisition device. The invention has the advantages of high detection sensitivity, fast response speed, and the like and can realize fast, accurate and long-term on-line monitoring of trace toxic and harmful gases or other specific gases, in particular to accurate measurement and analysis of gases under some special detection environments, such as the strong electromagnetic environment, the radioactive environment, the environment in a gas-production coal mine which is not allowed to use a power supply device on site, and the like.

A system to acoustically monitor at least one wind power installation, wherein the wind power installation includes a plurality of components including at least rotor blades. The system may comprise a remote monitoring center and a first wind power installation. The first wind power installation includes a sound pick-up device to detect an operating acoustic spectrum generated by at least one of the components of the first wind power installation during operation thereof, and circuitry to detect when a deviation between the operating acoustic spectrum of the first wind power installation and a reference spectrum exceeds a threshold. The system, in one aspect, may further include communications circuitry to communicate a fault message to the remote monitoring center when the deviation exceeds a threshold. The system may also include a remote monitoring center to monitor the operation of the first wind power installation.

An acoustic sensor comprises at least one resonant element. A driver comprises an electrical coupling means and an electromagnetic field source arranged such that the electrical coupling means transfers currents to the electromagnetic field source. The electromagnetic field source produces an electromagnetic field that drives the resonant elements to produce acoustic waves directed to a predetermined part of a test sample. Also provided is an electromagnetic detector for receiving the acoustic spectrum omitted from a test sample and an electrical circuit connected to the drive around detector.

The invention provides a feature extraction method of a radiated noise signal of an underwater target, comprising the steps of: firstly researching a visualization method of an acoustic signal to obtain a time-frequency visual image; then carrying out visual feature extraction method research including feature extraction and image centre torque feature extraction based on image texture by regarding a spectrogram in the time-frequency visual image as a searched object; on the basis, respectively utilizing principal component analysis (PCA) and linear discrimination analysis (LDA) algorithms to carry out optimal selection and dimension reduction on the visual feature obtained by the method, and finally applying the visual feature to simulation of underwater target identification. The experimental results show that the average recognition rates of three types of underwater noise signals under the mixed feature can be up to 91.97%, and the recognition rates of the selected visual feature parameters are obviously improved compared with the feature parameters extracted by the conventional method.

The present invention provides a real-time estimation method and apparatus for Doppler parameter, used for automatically computing and processing Doppler parameter of current curve of motor tissue or bloodstream sound spectrogram in real time in ultrasonic diagnosis system. The method comprises circular steps of: selecting a section of data from the current curve with preset data buffer zone in turn to estimate present eka-cardiac cycle; determining present search threshold value of peak flow rate; searching present peak flow rate according to the threshold value and the eka-cardiac cycle. The search period is shortened and the search accuracy is improved by using peak search period especially in the search process of the peak flow rate. By employing the invention, the system has advantages of low cost, high real time performance and reliable result.

The invention discloses a method for processing a signal of a sound spectrogram image and a system therefor. The method comprises the steps: analyzing the frequency spectrum of a backwave Doppler signal to obtain a power spectrum of the Doppler signal along with the time variation; estimating the noise average power by the power spectrum; determining the noise suppression threshold according to the noise average power; comparing the power spectrum and the noise suppression threshold and performing noise suppression according to the comparison result to obtain a power spectrum after suppression; and limiting the power spectrum after suppression to input the logarithmic compression within dynamic range to obtain a compressed sound spectrogram. In the invention, the noise suppression threshold can be determined according to the estimated noise average power and used for judging and selecting for the noise suppression, thereby realizing the real-time suppression for the noise part of the sound spectrogram and improving the signal-to-noise ratio of the spectrogram.

The invention discloses a music audio classification method based on a convolutional recurrent neural network. The method comprises the following steps: S1, annotating music audios to obtain a music annotation data set; S2, enhancing the training data of the data set by adopting a music data enhancement method; S3, framing and windowing the audio signals of the music in the data set, and obtaininga Mel sound spectrum corresponding to the audio through short-time Fourier transform and Mel scale transform; S4, constructing a music audio classification model based on a convolutional recurrent neural network; S5, inputting the Mel sound spectrum of the training data into the music audio classification model based on a convolutional recurrent neural network for iterative training; and S6, inputting a Mel sound spectrum corresponding to the music, and predicting the label of the music. The method provided by the invention can improve the ability of the network to extract the sound spectrumfeatures, and obtain better music overall feature representation, thereby improving the accuracy of music audio classification.

The invention discloses a method for increasing the self-adjusting performance of ultrasonic Doppler imaging and an ultrasonic system thereof. The method comprises the following steps: performing down-sampling treatment to echoes, generating a down-sampling acoustic spectrum image; and calling the calculated Doppler spectrogram adjusted by the down-sampling acoustic spectrum image. The Doppler self-adjusting method of the invention adopts the mode of down-sampling to treat two-way parallel echoes, wherein one way uses the original echoes to obtain a spectrogram and the other way uses the original echoes to perform down-sampling and obtain a spectrogram. The PRF of the spectrogram obtained through down-sampling is reduced, thus the blood flow signal region can be expanded. When signal extension is searched, boundary research can be performed on the down-sampling spectrogram so as to avoid inaccurate decisions caused by the small blood flow signal region.

A system and method are disclosed for generating a reversed photoacoustic spectrum at a greater distance. A source may emit a beam to a target and a detector measures signals generated as a result of the beam being emitted on the target. By emitting a chopped/pulsed light beam to the target, it may be possible to determine the target's optical absorbance by monitoring the intensity of light collected at the detector at different wavelengths. As the wavelength of light is changed, the target may absorb or reject each optical frequency. Rejection may increase the intensity at the sensing element and absorption may decrease the intensity. Accordingly, an identifying spectrum of the target may be made with the intensity variation of the detector as a function of illuminating wavelength.

The present invention relates to a power converter (90) and a method of operating same. There are numerous advantages to operating power converters using a series resonant converter (1, 21). This approach is particularly suitable for minimising switching losses in the power converter when it is operated at high frequency. However, there are problems with the known converters in that they are prone to generate noise in the acoustic spectrum due to the fact that the converter stages are often operating at different frequencies. The present invention relates to a power converter and a method of operating same that enables the operating frequency of the converter to be controlled by a control circuit over a predetermined range of the resonant frequency. This allows reduction in acoustic noise generation and facilitates frequency smearing that will in turn reduce spectral peaks. This is achieved whilst maintaining output ripple within acceptable ranges.

The invention discloses an automatic aliasing judgment and Doppler imaging adjusting method and an ultrasonic system thereof. The method comprises the following steps of: acquiring a Doppler spectrogram; comparing strong and weak parameters of the whole field signals of the spectrogram with a threshold value and judging whether the spectrogram performs vein aliasing for multiple times or not; according to the characteristics of the spectrogram area signals, judging whether the spectrogram performs artery aliasing for multiple times or not; and if the vein aliasing judgment result and the artery aliasing judgment result perform aliasing for multiple times, judging that the Doppler spectrogram does not perform aliasing for multiple times. In the method, the influence of spectrogram forms on the judgment is taken into full consideration, so the aliasing judgment of a vein spectrogram is added, the probability of erroneous judgment is reduced, and the accuracy of the aliasing judgment is improved.