EP2717599B1 - Verfahren zur Audiosignalverarbeitung mit Modellierung der globalen Antwort des elektrodynamischen Lautsprechers - Google Patents

Verfahren zur Audiosignalverarbeitung mit Modellierung der globalen Antwort des elektrodynamischen Lautsprechers Download PDF

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EP2717599B1
EP2717599B1 EP13174690.1A EP13174690A EP2717599B1 EP 2717599 B1 EP2717599 B1 EP 2717599B1 EP 13174690 A EP13174690 A EP 13174690A EP 2717599 B1 EP2717599 B1 EP 2717599B1
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Prior art keywords
loudspeaker
audio signal
state vector
parameters
response
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French (fr)
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EP2717599A1 (de
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Vu Hoang Co Thuy
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Parrot Drones SAS
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Parrot SA
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R3/00—Circuits for transducers, loudspeakers or microphones
    • H04R3/04—Circuits for transducers, loudspeakers or microphones for correcting frequency response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R29/00—Monitoring arrangements; Testing arrangements
    • H04R29/001—Monitoring arrangements; Testing arrangements for loudspeakers
    • H04R29/003—Monitoring arrangements; Testing arrangements for loudspeakers of the moving-coil type

Definitions

  • the invention relates to a technique for processing an audio signal based on the estimation of the overall response of a loudspeaker intended to reproduce this audio signal, that is to say taking into account all the parameters electrical, mechanical and acoustic characteristics characterizing this response.
  • the excursion of the loudspeaker diaphragm that is, the amplitude of its displacement by relative to its equilibrium position, quickly becomes too important, with the risk of damage to the loudspeaker and, at the very least, the introduction of excessive distortion, clipping and saturation values which rapidly degrade rapidly. the quality of playback of the audio signal.
  • Another type of treatment that can be envisaged consists in applying to the audio signal a specific compensation filtering of the non-linearities introduced by the loudspeaker, in order to reduce the audio distortions and to provide a better quality of listening.
  • T / S "Thiele and Small”
  • T / S "Thiele and Small”
  • the response of the loudspeaker, especially in the low frequencies, can be described by a set of parameters, referenced uniformly by the loudspeaker manufacturers.
  • the EP 1 799 013 A1 describes a technique for predicting the behavior of a loudspeaker, based on the T / S parameters, to compensate for non-linearities of the loudspeaker and to reduce the audio distortions introduced into the acoustic signal delivered to the user.
  • T / S parameters are, however, considered as invariants, known a priori, so that the modeling of the response is fixed and can not take into account either the slow evolution of the parameters, due for example to their drift over time because of the aging of the components.
  • the US 2003/0142832 A1 describes a technique for adaptively estimating the parameters of a loudspeaker, including non-linear parameters, from the measurement of the current flowing through this loudspeaker, with implementation of a gradient descent algorithm.
  • This method requires a pre-determination of the parameters during a static calibration phase: during this calibration, the T / S parameters are calculated for different values of the position of the membrane (offset or offset with respect to the equilibrium position). ), with measurement of the impedance. Then, a measurement of the current is compared to an estimate of the same current (squared and filtered by a low-pass filter) to calculate the derivative of the error with respect to each parameter.
  • the technique also implements a gradient descent algorithm of the least mean square type (LMS).
  • LMS least mean square type
  • this method has the disadvantage of requiring a prior calibration phase with impedance measurements and application of a predetermined signal, which excludes a re-estimation of subsequent parameters, at least by a consumer user.
  • the simple gradient descent LMS algorithms do not take into account the measurement noises, which are inevitable, which makes the estimator rather inefficient in real cases of use.
  • the US 2008/0189087 A1 describes another technique for estimating the parameters of a loudspeaker, also of LMS type by gradient descent. More particularly, the method processes separately the estimation of the linear part and that of the nonlinear part. For this, the error signal used by the LMS algorithm (difference between the measured signal and the predicted signal) is processed in order to decorrelate the linear part and the nonlinear part.
  • This document also proposes to implement the estimator by applying as input a particular audio signal, modified by a comb filter selectively eliminating certain selected frequencies.
  • This technique has the same drawbacks as the previous one, in particular the need for a calibration from a modified input signal likely to alter the listening comfort of the user, which does not allow the user to operate. estimate during a musical listening, transparently for the user.
  • the processing applied to the audio signal may in particular be a compensation processing of the non-linearities of the loudspeaker response, as determined from the state vector delivered by the predictive filter estimator.
  • the processing applied to the audio signal may comprise: c1) calculating a current value of the loudspeaker excursion as a function of i) an amplification gain of the audio signal and ii) the loudspeaker response as determined from the state vector outputted by the predictive filter estimator; c2) comparing the current excursion value thus calculated with a maximum excursion value; and c3) calculating a possible attenuation of the amplification gain in case the current excursion value exceeds the maximum excursion value.
  • the state vector components may include additional acoustic parameter values representative of the loudspeaker response associated with a rear cavity provided with a decompression vent.
  • step b) the determination of the state vector of step b) and carried out on the fly from the current audio signal object of the treatment of step c) and reproduced by the loudspeaker, by collecting the electrical parameters at speaker terminals while playing this audio signal.
  • the method may then comprise the following steps: storing a sequence of samples of the audio signal for a predetermined duration; analyzing the sequence to calculate an energy parameter of the stored audio signal; if the calculated energy parameter is greater than a predetermined threshold, enabling the estimation by the predictive filter; if not, inhibit prediction filter estimation and retain the previously estimated state vector values.
  • the left half schematizes the electrical part of the loudspeaker, to which is applied a measurable excitation voltage, Umes, from an amplifier producing a current i, also measurable, passing through the coil of the loudspeaker.
  • the first report transformer BI schematizes the electrical conversion into mechanical force applied to the coil.
  • the report gyrator Sd schematizes the mechanical conversion (displacement of the speaker membrane) in acoustic pressure.
  • the first three parameters (R e , M ms and R eq ) are linear parameters, the equivalent mass M ms being even an invariant, assumed to be known according to the manufacturer's specifications.
  • R e and R eq which can be considered constant over a short period (the time of their estimation) are parameters that can drift progressively over time as a function of the rise in temperature of the voice coil. aging of components, etc. and they must therefore be re-evaluated at regular intervals.
  • X [R e , R eq , Bl 0 , Bl 1 , Bl 2 , K eq0 , K eq1 , K eq2 , L e0 , L e1 , L e2 , L e3 , L e4 ] T.
  • the displacement x which is an unmeasured parameter, will be a hidden variable of the estimator.
  • the present invention implements a Kalman filtering, and more precisely an extended Kalman filtering (EKF), of which we will re-outline the main lines below.
  • EKF extended Kalman filtering
  • the "Kalman filter” which is based on a widely known algorithm, is a state estimator comprising an infinite impulse response (IIR) filter that estimates the states of a dynamic system from a set of equations describing the behavior of the system and a series of observed measures.
  • IIR infinite impulse response
  • Such a filter makes it possible in particular to determine a "hidden state", which is a parameter not observed but essential for the estimation.
  • the first step is the prediction of the model at time k, from the state at time k-1, given by the following equations: Prediction ( a priori ) of the estimated state x k
  • k -1 F k x k -1
  • k - 1 F k ⁇ P k - 1
  • k -1 Covariance of innovation S k H k ⁇ P k
  • k x k
  • k ( I - K k H k ) P k
  • the Kalman estimate is optimal in the least squares sense of the hidden model.
  • Extended Kalman filtering consists of approximating these functions f and h by their partial derivatives during the computation of the covariance matrices (prediction matrix and update matrix), in order to locally linearize the model and to apply to it in each point the systems of Kalman filter prediction and update equations discussed above.
  • k - 1 , u k - 1 H k ⁇ h ⁇ x
  • a digitized audio signal E coming from a media player is reproduced acoustically by a loudspeaker 10 after digital / analog conversion (block 12) and amplification (block 14).
  • the response of the loudspeaker 10 is simulated by an extended Kalman filter algorithm (estimator of the block 16) using as input the signals 18 collected on the loudspeaker 10, these signals comprising the voltage Umes applied to the terminals of the loudspeaker by the amplifier 14 and the current i flowing in the voice coil of the loudspeaker.
  • block 20 schematizes the estimator of the Kalman filter based on the modeling of the response of the loudspeaker, block 22 the function h of the measurement equation and block 24 the comparison between estimated state and measured state, to derive an error signal for updating the dynamic model.
  • the measurement of the voltage across the loudspeaker constitutes the only component of the observation vector Umes n-1 .
  • the algorithm then calculates the derivative of the function h with respect to each of the components of the vector X: dh (X) / dBl0, dh (X) / dKeq0, ... which corresponds to the partial derivative of the estimated voltage, relative to each of the parameters of the model.
  • the estimate of the parameters of the loudspeaker model at time n is given by the state vector X n
  • n thus obtained can be used for various purposes.
  • the knowledge of the response of the loudspeaker, and in particular of the excursion x of the membrane may notably be used as input data to a limiter stage 26 ( Figure 2 ): the instantaneous value x of the excursion is compared to a determined threshold x max beyond which this excursion is considered too important, with the risk of damaging the loudspeaker, the appearance of distortions, etc. If the threshold is exceeded, the The limiter determines an attenuation gain, less than unity, that will be applied to the incident signal E to reduce its amplitude, so that the excursion remains within the allowed range.
  • Another treatment that can be applied to the audio signal is compensation for non-linearities (block 28). Indeed, insofar as the speaker response is modeled, it is possible to predict the nonlinearities of this response and to compensate for them by an appropriate inverse processing applied to the signal. Such treatment is in itself known, and for this reason it will not be described in more detail.
  • the extended Kalman estimator operates on the fly, directly from the current audio signal reproduced by the loudspeaker, by collecting the electrical parameters on this loudspeaker (voltage, current) during the reproduction of this audio signal.
  • the system can thus be used with a high-fidelity consumer installation, operating in a manner that is transparent to the user: there is no need to ask the user to reproduce a particular type of calibration signal (white noise, succession of tones, etc.) so that the algorithm can estimate the parameters of the loudspeaker, the latter can operate continuously while the music is played.
  • a particular type of calibration signal white noise, succession of tones, etc.
  • the algorithm can estimate the parameters of the loudspeaker, the latter can operate continuously while the music is played.
  • the signal played move this membrane sufficiently so that the estimate is the best possible.
  • the displacement of the membrane is calculated continuously by applying Equations (1) and (2) of the estimator (block 32), with speaker parameters which are fixed and correspond to the results of the last estimation made by the Kalman filter.
  • this effective value is greater than a given threshold x_seuil (block 34) for a number of consecutive times corresponding to the time T, then it is considered that the T last seconds of signal played are valid and the filter update is activated. Kalman so that it can use these last T seconds of signal to re-estimate the parameters of the response of the speaker.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Otolaryngology (AREA)
  • Circuit For Audible Band Transducer (AREA)
  • Audible-Bandwidth Dynamoelectric Transducers Other Than Pickups (AREA)
  • Details Of Audible-Bandwidth Transducers (AREA)
  • Obtaining Desirable Characteristics In Audible-Bandwidth Transducers (AREA)
  • Stereophonic System (AREA)

Claims (6)

  1. Verfahren zur Verarbeitung eines digitalen Audiosignals, das dazu bestimmt ist, von einer Ausstattung wiedergegeben zu werden, die einen elektrodynamischen Lautsprecher umfasst, dessen globale Antwort in Abhängigkeit von dem elektrischen Signal, das an seine Klemmen angelegt wird, von einer Einheit elektrischer, mechanischer und akustischer Parameter definiert ist,
    wobei dieses Verfahren Folgendes umfasst:
    a) das Bestimmen eines Beobachtungsvektors, der nur Messungen elektrischer Parameter umfasst, mit:
    • einer Messung der Spannung (U) an den Klemmen des Lautsprechers, und
    • einer Messung des Stroms (i), der den Lautsprecher durchquert,
    b) das Bestimmen eines Zustandsvektors (X) durch Anwenden der Spannungs- und Strommessungen an einen Schätzer mit prädiktivem Filter, das eine Darstellung eines dynamischen Modells des Lautsprechers enthält,
    wobei dieses prädiktive Filter ein erweitertes Kalman-Filter ist, das geeignet ist, zum:
    • Ausführen einer Vorhersage des Zustandsvektors (X), und
    • Abstimmen dieser Vorhersage durch Berechnung einer Spannungsschätzung (Uest) ausgehend von dem Zustandsvektor und dem gemessenen Strom, und Vergleichen dieser Schätzung mit der Messung der Spannung (Umes), und
    c) in Abhängigkeit von dem Zustandsvektor (X), Anwenden einer Behandlung an das Audiosignal,
    dadurch gekennzeichnet, dass die Komponenten des Zustandsvektors Folgendes umfassen:
    • Werte linearer Antwortparameter des Lautsprechers, die in der folgenden Gruppe enthalten sind: elektrischer Widerstand (Re) und mechanischer Widerstand (Req), und
    • polynomische Koeffizienten nicht linearer Antwortparameter des Lautsprechers, die in der folgenden Gruppe enthalten sind: Leistungsfaktor (B10, B11, B12), Federungssteifigkeit (Keq0, Keq1, Keq2) und elektrische Flussdichte (Le0, Le1, Le2, Le3, Le4).
  2. Verfahren nach Anspruch 1, bei dem die Behandlung, die an das Audiosignal angewandt wird, eine Kompensationsbehandlung der Nichtlinearitäten der Antwort des Lautsprechers ist, wie sie ausgehend von dem Zustandsvektor, der von dem Schätzer mit prädiktivem Filter geliefert wird, bestimmt werden.
  3. Verfahren nach Anspruch 1, bei dem die Behandlung, die an das Audiosignal angewandt wird, Folgendes umfasst:
    c1) die Berechnung eines aktuellen Auslenkungswerts (x) des Lautsprechers in Abhängigkeit i) von einer Verstärkungszunahme des Audiosignals und ii) der Antwort des Lautsprechers, wie sie ausgehend von dem Zustandsvektor, der von dem Schätzer mit prädiktivem Filter geliefert wird, bestimmt wird,
    c2) das Vergleichen des derart berechneten aktuellen Auslenkungswerts mit einem maximalen Auslenkungswert, und
    c3) die Berechnung einer eventuellen Dämpfung der Verstärkungszunahme in dem Fall, in dem der aktuelle Auslenkungswert den maximalen Auslenkungswert überschreitet.
  4. Verfahren nach Anspruch 1, bei dem die Komponenten des Zustandsvektors (X) außerdem zusätzliche Werte akustischer Parameter umfassen, die für die Antwort des Lautsprechers, der mit einem hinteren Hohlraum, der mit einem Dekompressionsport versehen ist, assoziiert ist, repräsentativ sind.
  5. Verfahren nach Anspruch 1, bei dem die Bestimmung des Zustandsvektors des Schritts b) in Echtzeit ausgehend von dem aktuellen Audiosignal, das Gegenstand der Behandlung des Schritts c) ist, ausgeführt und von dem Lautsprecher durch Sammeln der elektrischen Parameter an den Klemmen des Lautsprechers während der Wiedergabe dieses Audiosignals wiedergegeben wird.
  6. Verfahren nach Anspruch 5, das die folgenden Schritte umfasst:
    - Speichern einer Probenabfolge des Audiosignals während einer vorbestimmten Dauer,
    - Analyse der Abfolge, um einen Energieparameter des gespeicherten Audiosignals zu berechnen,
    - falls der berechnete Energieparameter größer ist als ein vorbestimmter Schwellenwert, Aktivieren der Schätzung durch das prädiktive Filter,
    - im gegenteiligen Fall Inhibieren der Schätzung durch das prädiktive Filter und Beibehalten der Werte des Zustandsvektors, die zuvor geschätzt wurden.
EP13174690.1A 2012-08-30 2013-07-02 Verfahren zur Audiosignalverarbeitung mit Modellierung der globalen Antwort des elektrodynamischen Lautsprechers Not-in-force EP2717599B1 (de)

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FR1258116A FR2995167B1 (fr) 2012-08-30 2012-08-30 Procede de traitement d'un signal audio avec modelisation de la reponse globale du haut-parleur electrodynamique

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CN103686530A (zh) 2014-03-26
US20140064502A1 (en) 2014-03-06
EP2717599A1 (de) 2014-04-09
US9232311B2 (en) 2016-01-05
JP2014050106A (ja) 2014-03-17
FR2995167A1 (fr) 2014-03-07
FR2995167B1 (fr) 2014-11-14

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