147 results about "Time zero" patented technology

The invention relates to voice detection technology in an automatic caption generating system, in particular to a self-adaptive voice endpoint detection method. The method comprises the following steps: dividing an audio sampling sequence into frames with fixed lengths, and forming a frame sequence; extracting three audio characteristic parameters comprising short-time energy, short-time zero-crossing rate and short-time information entropy aiming at data of each frame; calculating short-time energy frequency values of the data of each frame according to the audio characteristic parameters, and forming a short-time energy frequency value sequence; analyzing the short-time energy frequency value sequence from the data of the first frame, and seeking for a pair of voice starting point and ending point; analyzing background noise, and if the background noise is changed, recalculating the audio characteristic parameters of the background noise, and updating the short-time energy frequency value sequence; and repeating the processes till the detection is finished. The method can carry out voice endpoint detection for the continuous voice under the condition that the background noise is changed frequently so as to improve the voice endpoint detection efficiency under a complex noise background.

The invention discloses a speaker recognition method based on depth learning. The method comprises the following steps: S1) carrying out pre-emphasis and overlapping-type framing windowing on collected voice signals; S2) carrying out endpoint detection on the collected voice signals by utilizing a dual-threshold endpoint detection method based on short-time energy and short-time zero-crossing rate, and judging and indentifying the staring moment, transition stage , noise section and ending moment of the voice; S3) carrying out feature extraction on the voice signals; S4) forming a depth belief network model based on restricted boltzmann machine hierarchy, training the established depth belief network model by utilizing layer-by-layer greedy algorithm and with speaker voice feature parameters being combined, and adding a Softmax classifier to the top layer of the depth belief network model; and S5) inputting the voice features of a speaker to the depth belief network model obtained after being subjected to training, calculating the probability that the model outputs voice features similar to the voice features of the other speakers, and selecting the speaker corresponding to the maximum probability as recognition result.

Temporally classifying and visually representing network and IT infrastructure with planned or occurred configuration activities and/or policy compliance or non-compliance of network and IT resources, including a method, apparatus and computer program for gathering and classifying observable configuration aspects of resources and relationships in a network of resources, wherein the method comprises: analyzing the network of resources to collect planned configuration times and actual resource status; monitoring actual resource status to make determinations if planned configurations are executed; and updating a network configuration status with the determinations. Planned and actual configurations are collected and monitored over a defined time range extending before and/or after a time zero. Each planned or actual configuration is categorized with respect to one or more time windows in the defined time range.

The invention discloses a high-efficiency voice detecting method. The method comprises the following steps: analyzing the short-time energy and the short-time zero-crossing rate of an original audio frequency on a time domain and removing parts of non-voice signals; analyzing the spectral envelop characteristic and the entropy characteristic of a preserved audio frequency signal subband on a frequency domain and further removing parts of non-voice signals; forming an audio frequency segment by continuous frames with similar characteristics in each preserved frame of audio frequency signals; calculating the average value of Mel-frequency Cepstral coefficient of each frame in each audio frequency, respectively inputting the average values into a voice gaussian mixture model and various non-voice gaussian mixture models, and performing band-level judgment on whether the audio frequency segment contains voice data according to the output probability of each model, thereby finally obtaining a voice detecting result. The method is capable of detecting voice signals from audio frequency data streams under various complex environments, and positioning the boundary between voice segment data and non-voice segment data relatively correctly.

The invention provides a method for determining a zero crossing point of an alternating current signal and a system for determining the zero crossing point of the alternating current signal. The method for determining the zero crossing point of the alternating current signal comprises the following steps: recording lasting time of the output zero crossing point of the alternating current signal, which is detected last time; calculating according to the lasting time and determining reference time of a next-time zero crossing point moment of the alternating current signal; and when a zero crossing signal is detected next time, determining the moment of the next-time zero crossing point moment of the alternating current signal according to the moment of the zero crossing signal detected next time and the reference time. According to the technical scheme, the detection precision of the zero crossing point is effectively improved under the precondition that hardware cost is not increased.

The present invention describes methods and apparatus for reliably assuring that correct mirror currents are selected during a channel switch to achieve the desired wavelength channel, based on feedback from either internal or external means combined with a mode map obtained at a time zero calibration.

The invention provides a timer and an implement method that is used for a multi-task system. The timer comprises a setup unit, a timing unit, a counting unit and an execution unit. The setup unit is used for setting up the timing time and the time zero of multiple tasks. The timing unit is used for setting up a timing cycle according to the timing time of the multiple tasks. The counting unit is used for setting up maximum timing count based on the timing time and the timing cycle of the multiple tasks; counts numbers according to the time zero and sends out the information of task execution at the end of timing time. The execution unit is used for receiving the information of the task execution and executing the task corresponding to the task execution information by a preset method according to the task execution information. In the invention, only a timer can perform reasonable and orderly management for the multiple masks in the system, thus reducing system resource occupied by the timer, improving system execution efficiency and decreasing difficulty in testing and maintaining the timer.

Detecting infectious messages comprises performing an individual characteristic analysis of a message to determine whether the message is suspicious, determining whether a similar message has been noted previously in the event that the message is determined to be suspicious, classifying the message according to its individual characteristics and its similarity to the noted message in the event that a similar message has been noted previously.

A voice recognizing method and system based on the phoneme includes: A) the analog voice signal is transferred into digital voice signal; B) the short-time zero-crossing ratio is detected, if the short-time zero-crossing ratio is less than the preset value, it is judged to sonant to processed as sonant, if the short-time zero-crossing ratio is higher than the preset value, it is judged to surd to processed as surd; C) the data after pretreatment is spectrum transformed to pick up character; D) the character data is analyzed; E) the phoneme sequence is output according to the analyzed result. The voice recognizing method and system can introduce different process method to surd and sonant, specially the sonant phoneme is modeled based on the single keynote cycle spectrum; it resolves the defect of current voice input recognizing system. It possesses advantages of high recognizing efficiency, high accuracy and high stability.

Non-volatile latch circuits, such as in memory cells and flip-flops, that are constructed for reliability screening. The non-volatile latch circuits each include ferroelectric capacitors coupled to storage nodes, for example at the outputs of cross-coupled inverters. Separate plate lines are connected to the ferroelectric capacitors of the complementary storage nodes. A time-zero test of the latch stability margin is performed by setting a logic state at the storage nodes, then programming the state into the ferroelectric capacitors by polarization. After power-down, the plate lines are biased with a differential voltage relative to one another, and the latch is then powered up to attempt recall of the programmed state. The differential voltage disturbs the recall, and provides a measure of the cell margin and its later-life reliability.

The invention provides an encoding method and a decoding method of voice frequency data. The encoding method comprises acquiring original voice frequency, carrying out endpoint detection through short-time energy and a short-time zero-crossing rate, eliminating non-voice-frequency data in the original voice frequency, and then acquiring voice section data; collecting characteristic parameters from the voice section data, recognizing statuses of each frame of the voice section data through trained hidden Markov model and Viterbi algorithm, and then confirming status switch and status duration; and encoding the status switch and the status duration, and then a voice frequency data package is generated. The encoding method and the decoding method of the voice frequency data can maintain high voice quality under the condition of low encoding rates.

The invention discloses a voice signal endpoint detection method based on a characteristic value code. Characteristic parameters including a short-time energy and a short-time zero-crossing rate are extracted in frames, an average value of the short-time energy, an average value of the short-time zero-crossing rate and a maximal value of the short-time zero-crossing rate are calculated, four thresholds are set for the short-time energy via a statistical result and empirical parameters, one threshold is set for the short-time zero-crossing rate, a voice characteristic is coded according to the thresholds, and endpoint detection is carried out on a voice signal according to five-grade determination rules on the basis of the characteristic value code of each frame. The lowest threshold is set for the short-time energy of an audio segment, suspected voices are accepted/rejected according to the rules by combining characteristics of the adjacent frames, the five-grade determination rules can handle with different complex conditions effectively, false detection and neglected detection are avoided, and the correct rate of endpoint detection of the voice signal can be improved substantially.

An embodiment of the invention relates to the technical field of automatic driving, and discloses a vehicle, and a method and a system for automatically calibrating zero offset of a steering wheel ofthe vehicle. The method includes judging whether the vehicle is in straight driving states in current sampling time intervals or not; determining that the current sampling time intervals are current calibration time intervals if the vehicle is in the straight driving states, and acquiring steering angles of the steering wheel of the vehicle when the vehicle is in the straight driving states; acquiring historical zero offset calibration results; calculating real-time zero offset calibration results of the steering wheel of the vehicle according to the historical zero offset calibration resultsand zero offset calibration results, which correspond to the current calibration time intervals, of the steering wheel of the vehicle. The steering angles are used as the zero offset calibration results, which correspond to the current calibration time intervals, of the steering wheel of the vehicle. The vehicle, the method and the system in the embodiment of the invention have the advantages thatthe zero offset of the steering wheel of the vehicle which is currently automatically driven can be automatically calibrated by the aid of the method and the system, and the zero offset measurement accuracy of the steering wheel of the vehicle can be improved.

The invention discloses a method for detecting a straddle type joint type turnout. The method comprises the following steps: 1) data collecting, 2) data displaying, 3) failure warning, 4) unlocking and locking timing, 5) straightening and bending timing, 6) turnout track timing, 7) turnout track counting and failure accumulating, and 8) failure accumulating time zero clearing. According to the method, switch single information of more turnout control systems is expanded, the time for maintaining and overhauling the turnout is shortened, and the method mainly completes the functions such as turnout failure control, turnout track counting, turnout failure track counting, touch screen image switching, unlocking and locking timing, straightening and bending timing, turnout track timing, and signal real-time display.

A rotorcraft early-warning device comprises a plurality of sound processing modules (1) and a positioning processing module (2); abnormal end point detection modules (5) are used for judging one of a sound short time average amplitude and a sound short time zero-crossing rate which exceed a threshold as abnormal sounds; the positioning processing module (2) comprises a time delay calculating unit (9) used for calculating a time delay difference that signals of the same sound source reach two sound processing modules (1), an angle calculating unit (10) used for determining a sound source directional angle according to the time delay difference and a geometrical relationship among intervals of the sound processing modules and a sound source positioning unit (11) used for positioning a sound source through combination of multiple groups of sound processing modules; the sound source positioning unit (11) is used for clustering according to an azimuth angle theta, selecting a sound source azimuth angle theta judged by two groups of sound processing modules with highest noise power after clustering as a final sound source direction, displaying the sound source position on an electronic map and giving an alarm.

The invention relates to voice detection technology in an automatic caption generating system, in particular to a method for extracting a short-time energy frequency value in voice endpoint detection. The method comprises the following steps: dividing an audio sampling sequence into frames with fixed lengths, and forming a frame sequence; extracting three audio characteristic parameters comprising short-time energy, short-time zero-crossing rate and short-time information entropy aiming at data of each frame; and calculating short-time energy frequency values of the data of each frame according to the audio characteristic parameters, and forming a short-time energy frequency value sequence. By combining the audio characteristic parameters of a time domain and a frequency domain, the method can develop respective advantages of the characteristic parameters, and can avoid respective disadvantages to a certain extent at the same time so as to effectively treat background noise of various different types.

The syllable division of Tibetan speech is an important part and essential link in Tibetan speech information processing, and lays the foundation for Tibetan speech recognition and speech database making; however, a software for the syllable division of Tibetan speech is still absent. Through extracting the time domain parameter short-time energy and short-time zero-crossing rate of Anduo Tibetan speech, the invention realizes Tibetan syllable division through a specific algorithm. The invention is used to carry out syllable division of 30 continuous Anduo Tibetan speech samples, and the division accuracy reaches to 30.6 percent.

The invention discloses a method and device for recognizing human voices in audio. The method comprises the steps that framing processing is carried out on audio data; each frame of the audio data after the framing processing is analyzed by using LPC with an order of P, and audio characteristics are extracted, and comprise a short-time zero-crossing rate, a P-order LPC predication coefficient and the skewness and the kurtosis of an LPC predicted residual magnitude spectrum; a P+3-order characteristic vector is formed according to the audio characteristics; an SVM algorithm is used for training the characteristic vector to obtain a corresponding support vector machine; whether the human voices are included in each frame of the audio data or not is recognized according to the support vector machine. According to the method and device for recognizing the human voices in the audio, the high-precision high-confidence reorganization on the human voices in the audio can be achieved, fundamental services are provided for song content analysis, and therefore the functions of lyric synchronization, song classification, song recommendation and the like are further achieved.

The invention discloses a noise diagnosis method for an electrical equipment break-down arc. The method comprises the following steps that A, an arc sound signal of the electrical equipment is collected, and pre-emphasis processing, FIR digital filtering and framing are carried out on the arc sound signal; B, short-time energy and short-time zero-crossing rate of each frame of the arc sound signalare calculated, short-time average energy and short-time average zero-crossing rate are determined, and an arc sound signal abnormal interval is detected by adopting a dual threshold determinate method; C, filtering is carried out on the arc sound signal abnormal interval by adopting M FIR filters, an energy value of each frequency domain sub-band is calculated to form an M-dimensional feature vector; D, a primary linear kernel model is established by using sample set data and an optimal parameter of a kernel function, an optimal linear kernel model is obtained by modifying the parameter repeatedly, the M-dimensional feature vector is diagnosed by using the optimal linear kernel model to determine whether or not a running state of the electrical equipment is normal. The noise diagnosis method for the electrical equipment break-down arc has the advantages that on-line detection and real-time alarming of the running state of the electrical equipment are achieved, and the damage and probability of the break-down arc are reduced.

The invention is a seismic acquisition vibroseis pseudo random scanning signal generating method in geophysical exploration. The method comprises the following steps: a Gold sequence code is generated according to the length of to-be-generated Num groups of vibroseis pseudo random scanning signals to obtain a target amplitude spectrum; windowing processing is performed on cross-correlation and autocorrelation of the Num groups of amplitude spectrum shaping signals in a time domain to obtain Num groups of pressed reconstruction signals; the maximum value of cross-correlation between each Num group of high-cut filter signals on the same time point position is divided by the minimum value of autocorrelation of each group of signals at the time zero to obtain the maximum relative cross-correlation value of the Num groups of high-cut filter signals; and iterative modification is performed to generate the final Num groups of vibroseis pseudo random scanning signals. The method of the invention enables the cross-correlation effect between the groups of pseudo random signals to be weak, thereby inhibiting adjacent gun interference in the efficient acquisition process, and improving the separation quality of shot records. The instantaneous frequency energy does not vary monotonically with time, which can greatly reduce the risk of resonance of surrounding buildings in the vibroseis construction process.