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WO2018130742A1 - Procédé de détermination de fréquences de spectres linéaires - Google Patents

Procédé de détermination de fréquences de spectres linéaires Download PDF

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Publication number
WO2018130742A1
WO2018130742A1 PCT/FI2017/050939 FI2017050939W WO2018130742A1 WO 2018130742 A1 WO2018130742 A1 WO 2018130742A1 FI 2017050939 W FI2017050939 W FI 2017050939W WO 2018130742 A1 WO2018130742 A1 WO 2018130742A1
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Prior art keywords
polynomial
sum
coefficients
line spectral
product order
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English (en)
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Adriana Vasilache
Anssi RÄMÖ
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Nokia Technologies Oy
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Nokia Technologies Oy
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/06—Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients
    • G10L19/07—Line spectrum pair [LSP] vocoders
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques

Definitions

  • the present invention relates to speech encoding methods, and in particular, to linear predictive coding (LPC) speech and audio coding techniques that employ line spectral frequency representation of a LPC filter.
  • LPC linear predictive coding
  • LPC Linear predictive coding
  • LSF Line Spectral Frequencies
  • a method for determining line spectral pairs for a linear prediction filter whose filter coefficients are linear predictive coefficients determined over a frame of audio samples, wherein the linear prediction filter is expressed as symmetric and antisymmetric polynomials, the zeros of which determine the line spectral pairs of the LP filter, comprising for each symmetric and antisymmetric polynomial: expanding the polynomial into an expanded polynomial; arranging each coefficient of a plurality of coefficients of the expanded polynomial into at least one sum of terms of the same product order; arranging the plurality of coefficients of the expanded polynomial into a linear system of equations and solving the linear system of equations to give a value for the at least one sum of terms of the same product order for each of the plurality of coefficients; forming a further polynomial, wherein a coefficient of the further polynomial is a value for at least one sum of terms
  • Arranging the coefficients into a linear system of equations may further comprise equating the at least one sum of terms of the same product order to a coefficient of the polynomial.
  • Solving the linear system of equations to give a value for the at least one sum of terms of the same product order may be solved in a recursive manner. Solving the further polynomial may comprise using Horner's method.
  • the at least one sum of terms of the same product may be a sum of line spectral pairs of the same product order.
  • the further polynomial can be a general polynomial of the form
  • prediction filter order k as and were in p k is a linear spectral
  • an apparatus configured to determine line spectral pairs for a linear prediction filter whose filter coefficients are linear predictive coefficients determined over a frame of audio samples, wherein the linear prediction filter is expressed as symmetric and antisymmetric polynomials, the zeros of which determine the line spectral pairs of the LP filter, wherein the apparatus is configured to for each symmetric and antisymmetric polynomial: expand the polynomial into an expanded polynomial; arrange each coefficient of a plurality of coefficients of the expanded polynomial into at least one sum of terms of the same product order; arrange the plurality of coefficients of the expanded polynomial into a linear system of equations and solving the linear system of equations to give a value for the at least one sum of terms of the same product order for each of the plurality of coefficients; form a further polynomial, wherein a coefficient of the further polynomial is a value for at least one sum of terms of the same product order for a coefficient of the expanded polynomial; and
  • the apparatus configured to arrange the coefficients into a linear system of equations may be further configured to equate the at least one sum of terms of the same product order to a coefficient of the polynomial.
  • the apparatus configured to solve the linear system of equations to give a value for the at least one sum of terms of the same product order may be configured to solve the linear system of equations in a recursive manner.
  • the apparatus configured to solve the further polynomial can be configured to use Horner's method.
  • the at least one sum of terms of the same product order may be a sum of line spectral pairs of the same product order.
  • Tthe further polynomial may be a general polynomial of the form
  • an apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to determine line spectral pairs for a linear prediction filter whose filter coefficients are linear predictive coefficients determined over a frame of audio samples, wherein the linear prediction filter is expressed as symmetric and antisymmetric polynomials, the zeros of which determine the line spectral pairs of the LP filter, wherein the apparatus is caused to for each symmetric and antisymmetric polynomial: expand the polynomial into an expanded polynomial; arrange each coefficient of a plurality of coefficients of the expanded polynomial into at least one sum of terms of the same product order; arrange the plurality of coefficients of the expanded polynomial into a linear system of equations and solving the linear system of equations to give a value for the at least one sum of terms of the same product order for each of the plurality of coefficients; form a further polynomial, wherein a coefficient
  • the apparatus caused to solve the linear system of equations to give a value for the at least one sum of terms of the same product order may be caused to solve the linear system of equations in a recursive manner.
  • the apparatus caused to solve the further polynomial can be caused to use Horner's method.
  • the at least one sum of terms of the same product order may be a sum of line spectral pairs of the same product order.
  • Tthe further polynomial may be a general polynomial of the form
  • the at least one sum of line spectral pairs of product order three imay be
  • a computer-readable medium having computer-readable code stored thereon, the computer readable code, when executed by a least one processor, causing an apparatus to: determine line spectral pairs for a linear prediction filter whose filter coefficients are linear predictive coefficients determined over a frame of audio samples, wherein the linear prediction filter is expressed as symmetric and antisymmetric polynomials, the zeros of which determine the line spectral pairs of the LP filter, wherein the apparatus is caused to for each symmetric and antisymmetric polynomial: expand the polynomial into an expanded polynomial; arrange each coefficient of a plurality of coefficients of the expanded polynomial into at least one sum of terms of the same product order; arrange the plurality of coefficients of the expanded polynomial into a linear system of equations and solving the linear system of equations to give a value for the at least one sum of terms of the same product order for each of the plurality of coefficients; form a further polynomial, wherein a coefficient of the further polynomi
  • the computer-readable medium having computer-readable code stored thereon, which causes the apparatus to solve the linear system of equations to give a value for the at least one sum of terms of the same product order may cause the apparatus to solve the linear system of equations in a recursive manner.
  • the computer-readable medium having computer-readable code stored thereon, which causes the apparatus to solve the further polynomial can cause to the apparatus to use Horner's method.
  • the at least one sum of terms of the same product order may be a sum of line spectral pairs of the same product order.
  • the further polynomial may be a general polynomial of the form
  • the at least one sum of line spectral pairs of product order three imay be
  • Figure 1 shows schematically an electronic device employing some embodiments
  • FIG. 2 shows schematically an audio codec system according to some embodiments
  • Figure 3 shows schematically a simplified encoder as shown in Figure 2 according to some embodiments.
  • Figure 4 shows a flow diagram illustrating the process of determining line spectral pairs according to embodiments.
  • the invention proceeds from the consideration that the procedure for calculating the line spectral frequencies in existing speech and audio codecs can be computationally expensive, and that there is a need to reduce this burden.
  • FIG. 1 shows a schematic block diagram of an exemplary electronic device or apparatus 10, which may incorporate a codec according to an embodiment of the application.
  • the apparatus 10 may for example be a mobile terminal or user equipment of a wireless communication system.
  • the apparatus 10 may be an audio-video device such as video camera, a Television (TV) receiver, audio recorder or audio player such as a mp3 recorder/player, a media recorder (also known as a mp4 recorder/player), or any computer suitable for the processing of audio signals.
  • TV Television
  • audio recorder or audio player such as a mp3 recorder/player, a media recorder (also known as a mp4 recorder/player), or any computer suitable for the processing of audio signals.
  • mp3 recorder/player such as a mp3 recorder/player
  • media recorder also known as a mp4 recorder/player
  • the electronic device or apparatus 10 in some embodiments comprises a microphone 1 1 , which is linked via an analogue-to-digital converter (ADC) 14 to a processor 21 .
  • the processor 21 is further linked via a digital-to-analogue (DAC) converter 32 to loudspeakers 33.
  • the processor 21 is further linked to a transceiver (RX/TX) 13, to a user interface (Ul) 15 and to a memory 22.
  • the processor 21 can in some embodiments be configured to execute various program codes.
  • the implemented program codes in some embodiments comprise a multichannel or stereo encoding or decoding code as described herein.
  • the implemented program codes 23 can in some embodiments be stored for example in the memory 22 for retrieval by the processor 21 whenever needed.
  • the memory 22 could further provide a section 24 for storing data, for example data that has been encoded in accordance with the application.
  • the encoding and decoding code in embodiments can be implemented in hardware and/or firmware.
  • the user interface 15 enables a user to input commands to the electronic device 10, for example via a keypad, and/or to obtain information from the electronic device 10, for example via a display. In some embodiments a touch screen may provide both input and output functions for the user interface.
  • the apparatus 10 in some embodiments comprises a transceiver 13 suitable for enabling communication with other apparatus, for example via a wireless communication network.
  • a user of the apparatus 10 for example can use the microphone 1 1 for inputting speech or other audio signals that are to be transmitted to some other apparatus or that are to be stored in the data section 24 of the memory 22.
  • a corresponding application in some embodiments can be activated to this end by the user via the user interface 15. This application in these embodiments can be performed by the processor 21 , causes the processor 21 to execute the encoding code stored in the memory 22.
  • the analogue-to-digital converter (ADC) 14 in some embodiments converts the input analogue audio signal into a digital audio signal and provides the digital audio signal to the processor 21 .
  • the microphone 1 1 can comprise an integrated microphone and ADC function and provide digital audio signals directly to the processor for processing.
  • the processor 21 in such embodiments then processes the digital audio signal in the same way as described with reference to the system shown in Figure 2 and the encoder shown in Figures 3.
  • the resulting bit stream can in some embodiments be provided to the transceiver 13 for transmission to another apparatus.
  • the coded audio data in some embodiments can be stored in the data section 24 of the memory 22, for instance for a later transmission or for a later presentation by the same apparatus 10.
  • the apparatus 10 in some embodiments can also receive a bit stream with correspondingly encoded data from another apparatus via the transceiver 13.
  • the processor 21 may execute the decoding program code stored in the memory 22.
  • the processor 21 in such embodiments decodes the received data, and provides the decoded data to a digital-to-analogue converter 32.
  • the digital-to- analogue converter 32 converts the digital decoded data into analogue audio data and can in some embodiments output the analogue audio via the loudspeakers 33.
  • Execution of the decoding program code in some embodiments can be triggered as well by an application called by the user via the user interface 15.
  • the received encoded data in some embodiment can also be stored instead of an immediate presentation via the loudspeakers 33 in the data section 24 of the memory 22, for instance for later decoding and presentation or decoding and forwarding to still another apparatus.
  • FIG. 2 The general operation of audio or speech codecs as employed by embodiments is shown in Figure 2.
  • speech and audio coding/decoding systems can comprise both an encoder and a decoder, as illustrated schematically in Figure 2.
  • some embodiments can implement one of either the encoder or decoder, or both the encoder and decoder.
  • Illustrated by Figure 2 is a system 102 with an encoder 104 and in particular a speech/audio signal encoder, a storage or media channel 106 and a decoder 108. It would be understood that as described above some embodiments can comprise or implement one of the encoder 104 or decoder 108 or both the encoder 104 and decoder 108.
  • the encoder 104 compresses an input audio/speech signal 1 10 producing a bit stream 1 12, which in some embodiments can be stored or transmitted through a media channel 106.
  • the encoder 104 furthermore can comprise a speech/audio encoder 151 as part of the overall encoding operation. It is to be understood that the speech/audio encoder may be part of the overall encoder 104 or a separate encoding module.
  • the bit stream 1 12 can be received within the decoder 108.
  • the decoder 108 decompresses the bit stream 1 12 and produces an output audio/speech signal 1 14.
  • the decoder 108 can comprise an audio/speech decoder as part of the overall decoding operation. It is to be understood that the audio/speech decoder may be part of the overall decoder 108 or a separate decoding module.
  • the bit rate of the bit stream 1 12 and the quality of the output audio signal 1 14 in relation to the input signal 1 10 are the main features which define the performance of the coding system 102.
  • Figure 3 shows schematically a simplified speech/audio encoder 104 according to some embodiments.
  • FIG. 3 shows a simplified speech/audio encoder 300, an example of an encoder 104 according to some embodiments. Furthermore with respect to Figure 4 the operation of at least part of the speech/audio encoder 300 is shown in further detail. It is to be appreciated that the simplified speech/audio encoder 300 as laid out in Figure 3 depicts a speech encoder conforming to the analysis-by-synthesis approach to speech coding, and that this coding approach only serves as an example into which the following line spectral frequencies determination method and apparatus can be deployed.
  • the following method and apparatus for determining the line spectral frequencies can be equally deployed in any speech/audio encoder which uses LP coefficients or reflection coefficients to represent at least part of a speech/audio signal.
  • the speech/audio encoder 300 is shown in Figure 3 as receiving the input speech/audio signal 1 10 via the audio sample framer 301 .
  • the audio sample framer 301 separates the input audio signal into frames of convenient length, typically of the order of tens of milliseconds.
  • the audio sample framer 301 may segment the input speech/audio signal into frames of 20ms, which equates to a frame of length 160 samples when the input speech/audio signal has a digital sampling rate of 8kHz.
  • the audio sample framer 301 can also be configured to perform a windowing operation over each frame, in order to smooth the speech/audio signal at the boundaries of each frame.
  • Each frame may then be passed to an LPC analyser 303.
  • the LPC analyser determines the LP coefficients for the frame. Typically the analysis of the input audio/speech frame is performed using the Levinson-Durbin algorithm in order to provide the LP coefficients.
  • the output of the LPC analyser 303 in other words the LP coefficients may then be transformed into Line Spectral Frequencies (LSF) by the LSF determiner 305.
  • LSFs are then typically quantised in preparation for transmission or storage by the LSF quantizer 307.
  • the quantized LSFs may then be interpolated with quantized LSFs from a previously processed speech/audio frame.
  • Interpolation of the quantized LSFs is depicted in Figure 3 as being performed by the LSF interpolator 309 in Figure 3.
  • Each speech/audio frame may be partitioned into a number of subframes. For instance by way of an example a 20ms speech frame may be partitioned into 4 subframes each of duration 5ms.
  • An LP analysis filter 31 1 can be constructed for each subframe by using a set of interpolated quantized LSFs from the LSF interpolator 309.
  • the next stage in an analysis-by-synthesis coding structure typically involves the determination of the pitch lag and pitch gain from the long term predictor 313.
  • a residual signal can then be generated by removing the long term predictor filter response from the speech/audio signal.
  • the residual signal is then typically encoded using an excitation codebook 315.
  • Quantized excitation codebook parameters along with quantized long term predictor parameters and quantized LSFs can be multiplexed by a multiplexer 317 into a bitstream 1 12 for transmission over a communication channel to a corresponding decoder 108.
  • LSF determiner 305 As depicted in Figure 3 in which the LPC coefficients are transformed to their corresponding Line Spectral Frequency (LSFs) values.
  • the LSFs may be derived by considering the nth degree predictor polynomial of the LP filter, n being the order of the LP filter. which satisfies the recurrence formula wherein are reflection coefficients.
  • the recurrence equation (2) is the
  • Levsinson-Durbin solution to the Yule-Walker equations It expresses the relationship between the (n+1 )th and the nth degree predictor polynomials. For the purpose of this description it is assumed that all roots of the predictor polynomial are inside the
  • the predictor polynomial is of a minimum phase.
  • LSP Line Spectral Pairs
  • LSP Line Spectral Pairs
  • equation (7) provide the odd numbered LSFs and equation (8) provides the even numbered LSFs. So from equation (7) it follows that the are the zeros of P(z) in the interval [ ⁇ , ⁇ ], and from equation (8) it follows that the are the zeros of Q(z) in the interval [0, ⁇ ] . It is to be noted that equation (7) provide the odd numbered LSFs and equation (8) provides the even numbered LSFs. So from equation (7) it follows that the are the zeros of P(z) in the interval [ ⁇ , ⁇ ], and from equation (8) it follows that the are the zeros of Q(z) in the interval [0, ⁇ ] . It is to be noted that equation (7) provide the odd numbered LSFs and equation (8) provides the even numbered LSFs. So from equation (7) it follows that the are the zeros of P(z) in the interval [ ⁇ , ⁇ ], and from equation (8) it follows that the are the zeros of Q(z) in the interval [0, ⁇ ] . It is
  • each of Q(z) and P(z) is half the order of the LP filter (or number of LP coefficients.)
  • the invention proceeds on the basis of expressing the coefficients of each of the equations P(z) and Q(z) in terms of the signed sum and product of the roots of P(z) and Q(z) respectively, noting that P(z) and Q(z) are both equations in z and the roots of P(z) and Q(z) are the Line Spectral Pairs p k , and then to use signed sum and products of the roots as the coefficients of a general form polynomial as given by equation (9).
  • the general form polynomials associated with the coefficients of P(z) and Q(z) respectively can then be each solved using a low complexity technique to produce the Line Spectral Pairs p k .
  • the general form polynomial associated with P(z) provides the odd ordered Line Spectral Pairs
  • the general form polynomial associated with Q(z) provides the even ordered Line Spectral Pairs.
  • equation P(z) to be evaluated can be represented as Expanding equation (10) as the product of k factors such that
  • equation (3) which is essentially a polynomial whose coefficients are derived directly from the coefficients of the LP filter system and since the LP filter coefficients are known, the above system of linear equations in (11 ) can be
  • the general polynomial will be of the form
  • the above general form polynomial can solved by the efficient procedure of nested multiplications, known as Horner's method (see, for example, Kincaid and Cheney, Numerical Analysis: Mathematics of Scientific Computing, Brooks/Cole Publishing Company, 1991 ).
  • Horner's method for solving the above general form polynomial, results in a significant reduction in instruction cycles when compared to the traditional method of using Chebyshev polynomials as mentioned above.
  • the method or apparatus configured to determine the line spectral pairs associated with a LP filter system herein has been laid out in terms of a specific example of an 8 th order LP filter system. It is to be further appreciated that the method or apparatus configured to determine herein described can be used to generate the line spectral pairs associated with other LP filter systems which have an even filter order. To that end there is shown below a Table 1 which lists the numerical weights associated with the coefficients for LP filter systems with filter orders up to
  • Some implementations may store the numerical weights associated with the coefficients for a particular LP filter order as a pre-calculated number rather than
  • FIG. 4 depicts the processing steps which can be executed as program codes on an apparatus 10 comprising a processor 21 for determining the line spectral pairs from the linear prediction coefficients in accordance with embodiments of the invention.
  • the LPC analyser 303 can be configured to analyze the short term correlations in the frame of speech/audio samples in order to determine the LP coefficients. Typically in embodiments this may take the form of computing a matrix of correlation values and then finding a solution to a set of linear equations.
  • the autocorrelation method may be used to derive the matrix of correlation values in which it is assumed that that the speech/audio samples lying outside the frame are zero.
  • the autocorrelation matrix is of a Toeplitz form leading to the use of the Levinson-Durbin algorithm for solving the set of linear equations therefore yielding the LP coefficients.
  • the covariance method may be used instead to derive the matrix of correlation values.
  • the matrix of correlation values is found by finding the cross correlation between two very similar but not identical, finite-length samples sequences, in other words the matrix of correlation values is generated by using sample values which lie outside the analysis window.
  • the correlation matrix is symmetrical about the leading diagonal, resulting in the use of efficient matrix inversion techniques such as Cholesky decomposition to solve the set of linear equations to find the LP coefficients.
  • FIG. 4 The step of deternnining the LP coefficients a j for a frame of Speech/audio samples is shown as processing step 401 in Figure 4.
  • the LP coefficients a j can be passed to the LSF determiner 305 for converting to their corresponding LSPs and ultimately to their corresponding LSFs.
  • the LSF determiner 305 is configured to determine the coefficients for each of the polynomials Q(z) and P(z) by using the LP coefficients a. j as determined by the previous processing stage 401 .
  • the coefficients for the symmetrical polynomial P(z) can be determined from the LP coefficients a. j by using equation (3), and the coefficients for the anti-symmetrical polynomial Q(z) can be determined from the LP coefficients a j by using equation (4).
  • these processing steps may be realized in C code as
  • the steps of determining the coefficients for the polynomials P(z) and Q(z) is shown as processing steps 403 and 405 in Figure 4.
  • the LSF determiner 305 can be configured to produce the numerical weights associated with the coefficients of for use in the solving of the linear system of
  • the processing step may be realized in C code as
  • the LSF determiner 305 can then be configured to solve a general polynomial of the form shown by equation (9) which is associated with the polynomial P(z) whose coefficients are the sum of the products as determined by the processing step
  • the LSF determiner 305 is also configured to solve the general polynomial associated with the polynomial Q(z) whose coefficients are the sum of the products ⁇ as determined by the processing step 41 1 . In each case the roots
  • the general polynomial associated with each of the polynomial P(z) and Q(z) can be solved using the computationally efficient Horner's method.
  • embodiments of the application operating within a codec within an apparatus 10
  • the invention as described above may be implemented as part of any audio (or speech) codec.
  • embodiments of the application may be implemented in an audio codec which may implement audio coding over fixed or wired communication paths, or for store and forward applications such as a music player.
  • the LP filter order together with the LSF and LSP orders used above are exemplary, and the codec may be configured to implement LP filter systems at other LP filter orders.
  • user equipment may comprise an audio codec such as those described in embodiments of the application above.
  • user equipment is intended to cover any suitable type of wireless user equipment, such as mobile telephones, portable data processing devices or portable web browsers.
  • elements of a public land mobile network may also comprise elements of a stereoscopic video capture and recording device as described above.
  • PLMN public land mobile network
  • the various embodiments of the application may be implemented in hardware or special purpose circuits, software, logic or any combination thereof.
  • some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto.
  • any blocks of the logic flow as in the Figures may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions.
  • the memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory.
  • the data processors may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASIC), gate level circuits and processors based on multi-core processor architecture, as non-limiting examples.
  • Embodiments of the application may be practiced in various components such as integrated circuit modules.
  • the design of integrated circuits is by and large a highly automated process. Complex and powerful software tools are available for converting a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate.
  • Programs can automatically route conductors and locate components on a semiconductor chip using well established rules of design as well as libraries of pre-stored design modules.
  • the resultant design in a standardized electronic format (e.g., Opus, GDSII, or the like) may be transmitted to a semiconductor fabrication facility or "fab" for fabrication.
  • the term 'circuitry' refers to all of the following:
  • circuits and software and/or firmware
  • combinations of circuits and software such as: (i) to a combination of processor(s) or (ii) to portions of processor(s)/software (including digital signal processor(s)), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions and
  • circuits such as a microprocessor(s) or a portion of a microprocessor(s), that require software or firmware for operation, even if the software or firmware is not physically present.
  • circuitry' applies to all uses of this term in this application, including any claims.
  • the term 'circuitry' would also cover an implementation of merely a processor (or multiple processors) or portion of a processor and its (or their) accompanying software and/or firmware.
  • the term 'circuitry' would also cover, for example and if applicable to the particular claim element, a baseband integrated circuit or applications processor integrated circuit for a mobile phone or similar integrated circuit in server, a cellular network device, or other network device.

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Abstract

L'invention concerne, entre autres, un procédé consistant : à déterminer des paires de spectres linéaires pour un filtre de prédiction linéaire dont les coefficients de filtre sont des coefficients prédictifs linéaires déterminés sur une trame d'échantillons audio, le filtre de prédiction linéaire étant exprimé sous la forme de polynômes symétriques et antisymétriques, dont les zéros déterminent les paires spectrales de ligne du filtre LP, consistant pour chaque polynôme symétrique et antisymétrique : à étendre le polynôme et agencer chaque coefficient d'une pluralité de coefficients du polynôme expansé en au moins une somme de termes du même ordre de produit ; à former un autre polynôme, un coefficient de l'autre polynôme étant une valeur d'au moins une somme de termes du même ordre de produit pour un coefficient du polynôme expansé ; et à résoudre l'autre polynôme dans lequel les racines de l'autre polynôme sont des paires de spectres linéaires.
PCT/FI2017/050939 2017-01-13 2017-12-27 Procédé de détermination de fréquences de spectres linéaires Ceased WO2018130742A1 (fr)

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EP17151305.4A EP3349212A1 (fr) 2017-01-13 2017-01-13 Procede de determination de frequences spectrales lineaires

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EP0774750A2 (fr) * 1995-11-15 1997-05-21 Nokia Mobile Phones Ltd. Détermination des fréquences du spectre de raies pour utilisation dans un radiotéléphone
WO2002003377A1 (fr) * 2000-07-05 2002-01-10 Koninklijke Philips Electronics N.V. Procede de calcul de frequences spectrales lineaires

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EP0774750A2 (fr) * 1995-11-15 1997-05-21 Nokia Mobile Phones Ltd. Détermination des fréquences du spectre de raies pour utilisation dans un radiotéléphone
WO2002003377A1 (fr) * 2000-07-05 2002-01-10 Koninklijke Philips Electronics N.V. Procede de calcul de frequences spectrales lineaires

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KABAL, P ET AL.: "The Computation of Line Spectral Frequencies Using Chebyshev Polynomials", IEEE TRANSACTIONS ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, vol. ASSP-34, no. 6, December 1986 (1986-12-01), pages 1419 - 1426, XP002066603 *

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