117 results about "Spectral coefficient" patented technology

A multi-mode audio signal decoder has a spectral value determinator to obtain sets of decoded spectral coefficients for a plurality of portions of an audio content and a spectrum processor configured to apply a spectral shaping to a set of spectral coefficients in dependence on a set of linear-prediction-domain parameters for a portion of the audio content encoded in a linear-prediction mode, and in dependence on a set of scale factor parameters for a portion of the audio content encoded in a frequency-domain mode. The audio signal decoder has a frequency-domain-to-time-domain converter configured to obtain a time-domain audio representation on the basis of a spectrally-shaped set of decoded spectral coefficients for a portion of the audio content encoded in the linear-prediction mode and for a portion of the audio content encoded in the frequency domain mode. An audio signal encoder is also described.

An audio signal decoder includes a transform domain path configured to obtain a time-domain representation of a portion of an audio content on the basis of a first set of spectral coefficients, a representation of an aliasing-cancellation stimulus signal and a plurality of linear-prediction-domain parameters. The transform domain path applies a spectrum shaping to the first set of spectral coefficients to obtain a spectrally-shaped version thereof. The transform domain path obtains a time-domain representation of the audio content on the basis of the spectrally-shaped version of the first set of spectral coefficients. The transform domain path includes an aliasing-cancellation stimulus filter to filter the aliasing-cancellation stimulus signal in dependence on at least a subset of the linear-prediction-domain parameters. The transform domain path also includes a combiner configured to combine the time-domain representation of the audio content with an aliasing-cancellation synthesis signal to obtain an aliasing reduced time-domain signal.

In a method for concealing an error in an encoded audio signal a set of spectral coefficients is subdivided into at least two sub-bands (14), whereupon the sub-bands are subjected to a re-verse transform (16). A specific prediction is performed (18) for each quasi time signal of a sub-band to obtain an estimated temporal representation for a sub-band of a set of spectral coefficients following the current set. A forward transform (20) of the time signal of each sub-band provides estimated spectral coefficients which can be used (28) instead of erroneous spectral coefficients of a following set of spectral coefficients, e.g. in order to conceal transmission errors. Transforming at the sub-band level provides independence from transform characteristics such as block length, window type and MDCT algorithm while at the same time preserving spectral processing for error concealment. Thus the spectral characteristics of audio signals can also be taken into account during error concealment.

A filter bank device for generating a complex spectral representation of a discrete-time signal includes a generator for generating a block-wise real spectral representation, which, for example, implements an MDCT, to obtain temporally successive blocks of real spectral coefficients. The output values of this spectral conversion device are fed to a post-processor for post-processing the block-wise real spectral representation to obtain an approximated complex spectral representation having successive blocks, each block having a set of complex approximated spectral coefficients, wherein a complex approximated spectral coefficient can be represented by a first partial spectral coefficient and by a second partial spectral coefficient, wherein at least one of the first and second partial spectral coefficients is determined by combining at least two real spectral coefficients. A good approximation for a complex spectral representation of the discrete-time signal is obtained by combining two real spectral coefficients, preferably by a weighted linear combination, wherein additionally more degrees of freedom for optimizing the entire system are available.

An audio signal encoder includes a transform-domain path which obtains spectral coefficients and noise-shaping information on the basis of a portion of the audio content, and which windows a time-domain representation of the audio content and applies a time-domain-to-frequency-domain conversion. The audio signal decoder includes a CELP path to obtain a code-excitation information and a LPD parameter information. A converter applies a predetermined asymmetric analysis window in both if a current portion is followed by a subsequent portion to be encoded in the transform-domain mode or in the CELP mode. Aliasing cancellation information is selectively provided in the later case.

The invention discloses a voice sensitive information detecting and filtering method based on unspecified people. The method is capable of detecting and filtering real-time voices and voice files. The method includes the steps: carrying out end point detection for an original voice through an improved double threshold end point detection algorithm, extracting the Mel frequency inverted spectral coefficient characteristic of the voice, training an appropriate voice characteristic template through a self-learning time warping algorithm, and storing the template in a database; and then performing end point detection for the original voice through the improved double threshold end point detection algorithm, extracting the MFCC characteristic, comparing the extracted voice characteristic with the template in the sensitive word characteristic template database by combining rough matching with fine matching, detecting sensitive words input to the voice, and filtering the detected sensitive words.

A method for calculating nonlinear function in counter quantization formula includes counting distribution probability of quantized spectral coefficient in code stream , calculating nonlinear function with table looking - up method in scope that occurrence probability of quantized spectral coefficient is relatively concentrated , using polynomial approximation to calculate nonlinear function is scope that occurrence probability of spectral coefficient is not relatively concentrated.

A coding efficiency of coding spectral coefficients of a spectrum of an audio signal is increased by en / decoding a currently to be en / decoded spectral coefficient by entropy en / decoding and, in doing so, performing the entropy en / decoding depending, in a context-adaptive manner, on a previously en / decoded spectral coefficient, while adjusting a relative spectral distance between the previously en / decoded spectral coefficient and the currently en / decoded spectral coefficient depending on an information concerning a shape of the spectrum. The information concerning the shape of the spectrum may have a measure of a pitch or periodicity of the audio signal, a measure of an inter-harmonic distance of the audio signal's spectrum and / or relative locations of formants and / or valleys of a spectral envelope of the spectrum, and on the basis of this knowledge, the spectral neighborhood which is exploited in order to form the context of the currently to be en / decoded spectral coefficients may be adapted to the thus determined shape of the spectrum, thereby enhancing the entropy coding efficiency.

A method for perceptual spectral decoding comprises decoding of spectral coefficients recovered from a binary flux into decoded spectral coefficients of an initial set of spectral coefficients. The initial set of spectral coefficients are spectrum filled. The spectrum filling comprises noise filling of spectral holes by setting spectral coefficients in the initial set of spectral coefficients not being decoded from the binary flux equal to elements derived from the decoded spectral coefficients. The set of reconstructed spectral coefficients of a frequency domain formed by the spectrum filling is converted into an audio signal of a time domain. A perceptual spectral decoder comprises a noise filler, operating according to the method for perceptual spectral decoding.

An apparatus for processing a multi-channel signal includes a means for determining a similarity between a first one of two channels and a second one of the two channels. Furthermore, a means for performing a prediction filtering of the spectral coefficients is provided, which is formed to perform a prediction filtering with only a single prediction filter for both channels in case of high similarity between the first and the second channel, and to perform a prediction filtering with two separate prediction filters in case of a dissimilarity between the first and the second channel. With this, an introduction of stereo artifacts and a deterioration of the coding gain in stereo coding techniques are avoided.

A method for improving noise robustness in speech recognition, wherein a front-end is used for extracting speech feature from an input speech and for providing a plurality of scaled spectral coefficients. The histogram of the scaled spectral coefficients is normalized to the histogram of a training set using Gaussian approximations. The normalized spectral coefficients are then converted into a set of cepstrum coefficients by a decorrelation module and further subjected to ceptral domain feature-vector normalization.

The signal processing is based on the c oncept of using a time-domain aliased (12, TDA) frame as a basis for time segmen tation (14) and spectral analysis (16), performing segmentation in time based on the time-domain aliased frame and performing spectral analysis based on the resulting time segments. The time resolution of the overall segmented time-to-frequenc y transform can thus be changed by simply adapting the time segmentation to ob tain a suitable number of time segments based on which spectral analysis is applied. The overall set of spectral coefficients, obtained for all the segments, provides a selectable time-frequency tiling of the original signal frame.

Provided is an audio encoding device that can suppress degradation of audio quality. Spectral coefficients of synthesized signal from CELP core layer are utilized to fulfill spectral gaps in error signal spectrum coefficients from a transform coding layer. By both spectral coefficients, decoded signal spectral coefficients are generated. The decoded signal spectral coefficients and the input signal spectral coefficients are divided into a plurality of sub bands. In each sub band, the energy of the input signal spectral coefficient corresponding to a zero decoded error signal spectral coefficient is calculated, and the energy of the decoded signal spectral coefficient corresponding to the zero decoding error signal spectral coefficient is calculated, and their energy ratio is calculated and is quantized and transmitted.

The invention relates to encoding of broadband and narrowband acoustic source signals (x) such that the perceived sound quality of corresponding reconstructed signals is improved in comparison to the known solutions. An enhancement estimation unit (102), operating in serial or in parallel with the regular encoding / decoding means (101), perceptually enhances a reconstructed acoustic source signal by utilisation of an enhancement spectrum (C) comprising a larger number of spectral coefficients than the number of sample values in corresponding frames of the signals carrying the basic encoded representation of the acoustic source signal. The thus extended block length of the enhancement spectrum frame provides a basis for accomplishing the desired improvement of the perceived sound quality.

An apparatus and method for adaptive sub-band allocation of spectral coefficients are disclosed. The sizes of sub-bands are determined according to the distribution of spectral coefficients transformed from an input speech / audio signal to perform more elaborate quantization in units of sub-bands. Thus, quantization noise of the spectral coefficients is reduced, and sound quality in a frequency region is enhanced, thereby improving the quality of the signal.

Modular radiance transfer pre-computes a spectral decomposition of a one bounce transport operator for each of a set of shapes and replaces a scene dependent direct-to-indirect transfer lighting computation with an art-directable mapping step. Modular radiance transfer provides an approach for rendering an approximate indirect lighting which requires small amounts of data, can be used to model very large (or even random scenes), and propagates much of the indirect lighting using a small number of spectral coefficients, so that rendering scales well to large scenes.

In the field of audio encoding / decoding technologies, a signal de-noising method is provided. The method includes: selecting, according to a degree of inter-frame correlation of a frame where a spectral coefficient to be adjusted resides, at least two spectral coefficients having high correlation with the spectral coefficient to be adjusted; performing weighting on the at least two selected spectral coefficients and the spectral coefficient to be adjusted to acquire a predicted value of the spectral coefficient to be adjusted; and adjusting a spectrum of a decoded signal by using the acquired predicted value, and outputting the adjusted decoded signal. A signal de-noising apparatus corresponding to the signal de-noising method and an audio decoding system using the signal de-noising apparatus are also provided.

The invention proposes a method and a device for arithmetic encoding of a current spectral coefficient using preceding spectral coefficients. Said preceding spectral coefficients are already encoded and both, said preceding and current spectral coefficients, are comprised in one or more quantized spectra resulting from quantizing time-frequency—transform of video, audio or speech signal sample values. Said method comprises processing the preceding spectral coefficients, using the processed preceding spectral coefficients for determining a context class being one of at least two different context classes, using the determined context class and a mapping from the at least two different context classes to at least two different probability density functions for determining the probability density function, and arithmetic encoding the current spectral coefficient based on the determined probability density function wherein processing the preceding spectral coefficients comprises non-uniformly quantizing absolutes of the preceding spectral coefficients for use in determining of the context class.

The method decomposes the radio frequency signal into sub-bands by filtering, for example with a time-frequency transform. From the coefficients acquired through decomposition a matrix of spectral coefficients is obtained, from which local estimators are obtained, constituted in particular by the coefficients of the interpolating polynomials. The statistical distribution of the local estimators is evaluated in windows overlaid on the ultrasound frame. The conformation of the distribution histograms of the spectral coefficients provides a parameter which, combined with the local estimators, provides weighted local estimators, which contain spectral information useful in the identification of specific structures in the organ subjected to ultrasound analysis.

The embodiment of the invention discloses a signal denoising method, a signal denoising device and an audio decoding system, which belong to the technical field of audio coding and decoding. The method provided by the embodiment of the invention comprises: selecting at least two spectral coefficients which have high relevance to a spectral coefficient to be adjusted according to the inter-frame relevance of the frame of the spectral coefficient to be adjusted; performing weighting by using the selected at least two spectral coefficients and the spectral coefficient to be adjusted and acquiring a predicted value of the spectral coefficient to be adjusted; and performing the spectral adjustment of a decoded signal by using the acquired predicted value and outputting an adjusted decoded signal. The embodiment of the invention also discloses a signal denoising device and an audio decoding system. Through the embodiment of the invention, the noises generated in frequency synthesis after decoding are reduced, and the auditory effect is improved.

The invention discloses a Bluetooth audio howling detection suppression method and device, a medium and Bluetooth equipment and belongs to the technical field of audio coding and decoding. The method comprises the following steps of calculating to obtain a pseudo-spectral coefficient corresponding to each spectral coefficient by using each spectral coefficient in current frame audio spectral coefficients obtained through discrete cosine transform in a Bluetooth audio coding and / or decoding process and two spectral coefficients adjacent to the spectral coefficient; calculating a sub-band energy entropy by using all pseudo-spectral coefficients corresponding to the current frame audio spectral coefficient to obtain a pseudo-spectral entropy of the current frame audio spectral coefficient; and judging whether the current frame audio spectrum coefficient contains howling or not by using the pseudo spectrum entropy of the current frame audio spectrum coefficient and a preset spectrum entropy threshold value. The howling detection method and device can avoid time-frequency transformation required by howling detection in the prior art, save the operand and reduce the system time delay.

The invention relates to a ring surface harmonic-analysis method on the basis of satellite gravity gradient observation data, which includes the following steps: preprocessing the satellite gravity gradient observation data, integrally reducing the satellite gravity gradient observation data to the same spherical surface and performing gridding process on the same to obtain regular grid average value; mapping the grid value on the spherical surface to the ring surface by means of mapping relation of the spherical surface to the ring surface, and obtaining circular regular grid value; perform spline analysis on the gravity gradient data on the ring surface, converting the regular grid average value on the ring surface into continuous spline approximating function; performing two-dimensional Fourier analysis on the gravity gradient on the ring surface, and converting spline approximation to determine Fourier coefficient; and computing the two-dimensional Fourier spectral coefficient of the ring surface into harmonic expansion coefficient. High-accuracy and high-efficiency self-consistency harmonic analysis of the satellite gravity gradient observation data is realized, the error caused by inaccuracy and the like of smoothing factors in existing harmonic analysis is overcome, and the ring surface harmonic-analysis method has the advantages of high computing speed and accuracy.