FR2942345A1 - Gesture interpreting device for player of e.g. guitar, has gesture interpretation and analyze sub-module assuring gesture detection confirmation function by comparing variation between two values in sample of signal with threshold value - Google Patents

Abstract

The device has a processing module for processing sampled signals in an output of an input module (10). An output module (30) reproduces musical signification of the gesture of a user. The processing module has a gesture interpretation and analyze sub-module (210) with a recursive low-pass filter to receive signals at an output of the input module. The sub-module assures a gesture detection function and a gesture detection confirmation function by comparing variation between two values in the sample of one of the signals of movement sensors e.g. accelerometer, with a threshold value. An independent claim is also included for a method for interpreting gesture of a user.

Description

The invention relates to the field of the interpretation of musical gestures or gestures acting on or as musical instruments. In particular, it relates to a device and a method for processing signals representative of the movements of a music player using an instrument or beating a rhythm of accompaniment. Devices and methods for play or learning have been developed to allow a musical instrument player using an object that simulates said instrument to play a partition, if necessary coupled with the scores of other instruments. The instruments whose interpretation is simulated can be a guitar, a piano, a saxophone, a drums .... In such devices, the scores of the score are generated from the player's actions. Such devices and methods can use buttons that trigger notes, if necessary by combining said buttons. Some devices such as WIITM Music also use a recognition of certain gestures of the musician with the pressure on the buttons to play the score. Since the WIITM Music motion sensor is an optical sensor that requires a fixed reference, its measurements are both conditioned by the player's position relative to the reference and rudimentary, which considerably limits the possibilities of interpretation. A satisfying musical rendering indeed requires a high accuracy of the capture of the movements of the player who are really intended to operate the instrument.

The present invention provides an answer to these limitations of the prior art by using motion sensors and a processing of their measurements that allow this accuracy and thus allow a satisfactory musical rendering.

For this purpose, the present invention discloses a device for interpreting gestures of a user comprising at least one measurement input module comprising at least one motion sensor, a module for processing sampled signals at the output of the module. input and an output module adapted to reproduce the musical meaning of said gestures, said device being characterized in that the signal processing module comprises a sub module for analyzing and interpreting gestures comprising at least a pair of two filters recursively successive low-pass receivers adapted to receive at least one of the output signals of the module, a significant gesture detection function and a significant gesture detection confirmation function by comparing the variation between two successive values in the sample at least one of the signals from the sensor group with at least one selected threshold value. Advantageously, the significant gesture detection function is able to identify sign changes between two successive values in the sample of the difference between at least one output of the first filter of at least one of the filter pairs at the current value and at least one output of the second filter of the same pair of filters for the same signal at the previous value.

Advantageously, the sub-module for analyzing and interpreting gestures further comprises a function for measuring the velocity of the gesture detected at the output of the detection confirmation function. Advantageously, the velocity measurement function is able to calculate the stroke (Max-Min) between two significant gestures detected.

Advantageously, the second filter is able to operate at a cutoff frequency lower than that of the first filter. Advantageously, the input module comprises at least a first accelerometer type sensor and a second sensor selected from the group of magnetometer type sensors and gyrometer.

Advantageously, the significant gesture detection function is able to receive at least one output of the second recursive filter of one of the pairs of filters applied to at least one of the signals of the first sensor. Advantageously, the significant gesture detection confirmation function is able to receive as input at least one output of the second recursive filter of one of the pairs of filters applied to at least one of the signals of the second sensor. Advantageously, the threshold chosen for the significant gesture detection confirmation function is of the order of 5/1000. Advantageously, the input module transmits to the processing module 35 only signals from a gyrometer type sensor.

Advantageously, the input module receives the signals from at least two sensors positioned on two independent parts of the body of the user, a first sensor providing via one of the pairs of recursive filters an input signal of the gesture detection function. significant and a second sensor providing via a pair of recursive filters an input signal of the gesture velocity measurement function detected at the output of the significant gesture detection confirmation function. Advantageously, the signal processing module comprises an input sub-module of pre-recorded multimedia contents.

Advantageously, the multimedia content input sub-module comprises a function of partitioning said multimedia time-slot contents that can be used to perform a second confirmation of detection of the significant gestures detected. Advantageously, the input module is able to transmit to the processing module a signal representative of the position of the user in a plane substantially orthogonal to the direction of the detected significant gesture to make a second confirmation.

The invention also discloses a method for interpreting significant gestures of a user comprising at least one measurement input step from at least one motion sensor, a signal processing step sampled at the output of the an input step and an output step adapted to reproduce the musical meaning of said gestures, said method being characterized in that the signal processing step comprises a sub-step of analysis and gesture interpretation comprising at least one pair of two successive low-pass recursive filterings of at least one of the signals, a significant gesture detection function and a significant gesture detection confirmation function by comparing the variation between two values in the sample of at least one of one of the signals from the sensor group with at least one selected threshold value.

Another advantage of the invention is that it uses micro sensors (accelerometers and magnetometers or gyrometers) at low cost. It can be used to play with the hands and / or beat the measure with the feet. It does not require a long learning and can be used by several players. It can be used with a large number of movements and instruments. It can also be used without any object simulating any instrument.

The invention will be better understood, its various features and advantages will emerge from the following description of several exemplary embodiments and its accompanying figures of which: Figure 1 represents different contexts of use of the invention 10 according to several embodiments; FIG. 2 is a simplified representation of a functional architecture of a device for interpreting musical gestures according to one embodiment of the invention; Fig. 3 (3a, 3b) shows a general flowchart of the treatments in one embodiment of the invention using an accelerometer and a magnetometer or a gyrometer; FIG. 4 represents a flow diagram of the filtering of the signals of the motion sensors in one embodiment of the invention; Fig. 5 shows a flowchart of the detection of the power of the motion sensor signals in one embodiment of the invention; Figure 6 shows a general flowchart of the treatments in one embodiment of the invention using only a gyrometer.

FIG. 1 shows three modalities 110, 120A and 120B of input of musical gestures in a processing module 20 for reproduction by a musical synthesis module 30. On the left of FIG. 1 are represented from top to bottom the three input modes 10 of musical gestures: 30 - A musician 110 plays a guitar on which have been fixed one or more motion sensors such as MotionPodTM MoveaTM; it is then the movements of the guitar that are measured by the motion sensors and supplied to the processing unit 20; A 120A musician directly carries motion sensors of the same type on a part of the body (hand, forearm, arm, foot, leg, thigh, etc.); he can play the score of an instrument or simply beat a rhythm; - A 120E musician can also operate a GyroMouseTM or a Movea AirMouseTM which is a three-dimensional remote control comprising a three-axis gyrometer for controlling a point moving on a used plane, offering the possibility of using either the movements of the point either the measurements ~ o of one or more axes gyrometers. A MotionPod comprises a tri-axis accelerometer, a tri-axis magnetometer, a pre-processing capability for preforming signals from the sensors, a radiofrequency transmission module of said signals to the processing module itself and a battery. This motion sensor 15 is called 3A3M (three accelerometer axes and three magnetometer axes). Accelerometers and magnetometers are small, low-cost, low-cost commercial micro-sensors, for example a KionixTM three-way accelerometer (KXPA4 3628) and HoneyWellTM magnetometers of the HMC1041Z type (1 vertical channel) and 20 HMC1042L for the 2 horizontal lanes. Other suppliers exist: MemsicTM or Asahi KaseiTM for magnetometers and STMTM, FreescaleTM, Analog DeviceTM for accelerometers, to name just a few. In the MotionPod, for the 6 signal channels, there is only one analog filtering and then, after digital analog conversion (12 bits), the raw signals are transmitted by a radio frequency protocol in the BluetoothTM band (2.4GHz ) optimized for consumption in this type of applications. The data is therefore raw to a controller that can receive data from a set of sensors. They are read by the controller and made available software. The sampling rate is adjustable. By default, it is set at 200 Hz. Higher values (up to 3000 Hz or more) can nevertheless be envisaged, allowing greater accuracy in the detection of shocks, for example. The radio frequency protocol of the MotionPod makes it possible to guarantee the provision of the data to the controller with a controlled delay, which should not exceed 35 10ms (at 200 Hz), which is important for the music.

An accelerometer of the above type makes it possible to measure longitudinal displacements along its three axes and, by transformation, angular displacements (except around the direction of the Earth's gravitational field) and orientations with respect to a Cartesian reference frame in three dimensions. A set of magnetometers of the above type makes it possible to measure the orientation of the sensor to which it is fixed with respect to the terrestrial magnetic field and thus displacements and orientations with respect to the three axes of the reference frame (except around the direction of the magnetic field earthly). The 3A3M combination provides complementary and smooth motion information. In fact, in the invention only the information relating to one of the axes, the vertical axis Z or one of the other two axes is used. We can therefore be satisfied in principle with a single-axis sensor of each type, when two types of sensors (accelerometer and magnetometer or accelerometer and gyrometer) are used. In practice, given the low cost availability of 3A3M sensor modules incorporating transmission and processing of the six channels, this is the preferred approach. Other motion sensors may be used, for example a combination of accelerometer and gyrometer (so-called 3A3G sensors) or even a single three-axis gyrometer, as explained below in the description in commentary to other figures. When several sets of motion sensors are used, the remote controller of the MotionPod (at the input of the processing module 20, 210) synthesizes the signals of the sensor assemblies. A compromise must be found between the number of sensors, the sampling frequency of the sensors and the energy consumption autonomy of the sensor assemblies. In the remainder of the description, the term "output signal of the accelerometer or magnetometer in the singular indifferently the outputs of the controller depending on whether the input data come from a single sensor module 3A3M or a set of modules 3A3M synthesized in the controller. The AirMouse includes two gyrometer type sensors, each with an axis of rotation. The gyrometers used are from the Epson reference XV3500. Their axes are orthogonal and deliver the pitch angles (yaw or rotation around the axis parallel to the horizontal axis of a plane facing the user of the AirMouse) and yaw (pitch or rotation around a axis parallel to the vertical axis of a plane facing the user of the AirMouse). The instantaneous pitch and yaw speeds measured by the two gyrometer axes are transmitted by radio frequency protocol to a controller of the input module (10) and converted by said controller in motion of a cursor in a screen facing the user. . In the application of the invention it is possible to use either one of the cursor control signals (in Z or Y), or both, or a direct measurement signal at the output of one of the gyrometer axes.

The functionalities and architecture of the processing module 20 will be commented on in connection with FIG. 2. An output module 30 reproduces the sounds produced by the combination of pre-recorded contents and the capture of the musical gestures produced by the player via the input module 10. It may be a simple speaker or a synthesizer.

The functional architecture of the device of the invention is described in FIG. 2. The modules 10 and 30 are not returned. The module 20 performs the processing of the signals received from the input module 10 within a module. gesture analysis and interpretation system 210 whose outputs are supplied to a module for calculating the control data of the musical content 230. A pre-recorded multimedia content is also provided by a module 220 to the module 230. To correctly specify the algorithm analysis and interpretation of the musical gestures implanted in the module 210, it is necessary to take into account the specificity of the said gestures. In particular, playing a 5 minute piece of music for example by beating a moderately fast tempo at 120 bpm (beat per minute) results in 600 beats performed by the user. However, in a musical context, a single error results in a rupture of meaning and a loss of interest in the device. In case of false alarm, the system detects non-existent beats, in case of non-detection obviously the play of the piece is interrupted. However, in situation of musical interpretation by beat of tempo, the user adopts a gesture on the one hand of his own, on the other hand admitting a certain variability within his own body language. Moreover, human-specific motor physiological phenomena, themselves dependent on the beat speed, are superimposed on this variability (we have a quasi-sinusoidal mode at high speed, but with strong rebounds at slow speed). These findings have several consequences: we must use algorithms achieving a fidelity of the order of 1 per 1000, a very high value in a context of little known variability (human expressive movement); the only accelerometers do not make it possible to reach such a performance, for at least two reasons (rebounds in case of w average or slow speed, difficulty to anticipate and thus to produce information of power of the correct movement), of where the choice made to use bimodal sensors; - The processing algorithms must be very adaptable. Moreover, it seems that the behavior of the user depends directly on his interaction with the content he is interpreting. It is therefore necessary to provide a process in situation, that is to say by putting the human system in an action / perception loop including all aspects involved (content, brain and cognitive, gestures, actuators, sensors. .). To meet these specifications, the general processing principle implemented in the module 210 has the following two characteristics: an adaptive processing to eliminate the components of the signals having slow variations (of the order of one second); using the outputs of a sensor (a magnetometer or a gyrometer) to detect a strike; The use of the outputs of the other sensor (the accelerometer or one of the measurements of the gyrometer if this sensor is used alone), to measure the intensity of the striking.

The module 220 makes it possible to insert pre-recorded contents of the MIDI 30 type (Musical Instrument Digital Interface) coming from an electronic musical instrument, audio coming from a reader (MP3 to MPEG (Moving Picture Expert Group) 1/2 Layer 3 , WAV to WAVeform audio format, WMA to Windows Media Audio, etc ...), multimedia, images, video, etc ... via a suitable interface. The outputs of the module 220 are provided concurrently with the module 210 (to allow consideration of the music player's reactions) and the module 230 to be subsequently reproduced at the output of the processing device.

The module 230 makes it possible to synthesize the musical gestures interpreted by the module 210 and the pre-recorded contents at the output of the module 220. The simplest mode is to play a fragment, for example, encoded in MP3 or midi file (or file video) every time a strike is detected by the module 210, which will then sequentially seek the fragments in the module 220. This mode allows ~ o many interesting applications. It is much more flexible and powerful than 220 integrates a method such as the one we disclosed in the application No. FR07 / 55244 entitled Computer-Assisted Music Interpretation System and held by the inventor of the present application . The device disclosed in this invention comprises two memories one of which comprises the musical data which define the totality of the musical events constituting the piece of music to be interpreted and the other the sequence of actions necessary for the reproduction of the stored musical events as well as means for establishing said musical information by comparing the data stored in the first memory of the musical data and the memory of the sequence of the actions. In this case, the user will have complete control over what he wants to play and when, and what is left to the initiative of the machine (eg an accompaniment).

Fig. 3 (cut at 3a and 3b for readability) represents a general flowchart of the treatments in one embodiment of the invention using an accelerometer and a magnetometer or a gyrometer. In the rest of the description relating to this figure, whenever the word magnetometer is used, it is indifferently denoted a magnetometer 30 or a gyrometer. All the treatments are done in software in the module 210.

The processes firstly comprise a low-pass filtering of the outputs of the sensors of the two modalities (accelerometer and magnetometer) whose detailed operation is explained in FIG. 4.

This filtering of the output signals of the motion sensor controller uses a recursive approach of order 1. The gain of the filter may for example be set at 0.3. In this case, the filter equation is given by the following formula: Output (z (n)) = 0.3 * Input (z (n-1)) + 0.7 * Output (z (n-1)) Where, for each of the modalities: z is the reading of the modality on the axis used; n is the reading of the current sample; n-1 is the reading of the previous sample.

The treatment then comprises a low-pass filtering of the two modalities with a cut-off frequency lower than that of the first filter. This lower cut-off frequency results from the choice of a coefficient of the second filter which is lower than the gain of the first filter. In the case chosen in the example above, where the coefficient of the first filter is 0.3, the coefficient of the second filter can be set at 0.1. The equation of the second filter is then (with the same notation as above): Output (z (n)) = 0.1 * Input (z (n-1)) + 0.9 * Output (z (n-1)) Then, the processing comprises a detection of a zero of the derivative of the output signal of the accelerometer with the measurement of the output signal of the magnetometer. The following notations are applied: A (n) the output signal of the accelerometer in the sample n; AF1 (n) the signal of the accelerometer at the output of the first recursive filter in the sample n; AF2 (n) the signal AF1 filtered again by the second recursive filter in the sample n; B (n) the magnetometer signal in sample n; - BF1 (n) the magnetometer signal at the output of the first recursive filter in the sample n; BF2 (n) the signal BF1 filtered again by the second recursive filter in the sample n. Then, the following equation allows to calculate a filtered derivative of the accelerometer signal in sample n: FDA (n) = AF1 (n) - AF2 (n-1) A negative sign of product FDA (n) * FDA (n-1) indicates a zero of the derivative of the filtered signal of the accelerometer and thus detects a strike.

For each of these zeros of the filtered signal of the accelerometer, the processing module checks the intensity of the deviation of the other modality at the filtered output of the magnetometer. If this value is too low, the strike is considered not as a primary strike but as a secondary or ternary strike and discarded. The threshold for discarding non-primary strikes depends on the expected amplitude of the deviation of the magnetometer. Typically, this value will be of the order of 5/1000 in the envisaged applications. This part of the treatment thus makes it possible to eliminate the insignificant strikes.

Finally, for all the primary keystrokes detected, the processing module 15 calculates a signal of velocity (or volume) of the strike by using the deviation of the filtered signal at the output of the magnetometer. The value DELTAB (n) is introduced into the sample n which can be considered as the pre-filtered signal of the centered magnetometer and which is calculated in the following manner: DELTAB (n) = BF1 (n) - BF2 (n) DELTAB (n) minimum and maximum values are stored between two primary keystrokes detected. An acceptable value VEL (n) of the velocity of a primary strike detected in a sample n is then given by the following equation: VEL (n) = Max {DELTAB (n), DELTAB (p)} - Min { DELTAB (n), DELTA (p)} Where p is the index of the sample in which the previous primary keystroke was detected. Velocity is thus the race (difference Max-Min) of the derivative of the signal between two detected primary strikes, characteristics of musical gestures. This part of the treatment is illustrated in FIG.

An adaptive processing is thus carried out because the processing of the magnetic modality includes a centering of the signal. The signal itself subtracts its own slow variations (see formula above). Thus, for example, if the user turns 60 ° to his right, the received magnetic signals will be shifted, but the corresponding offset will be removed by the subtraction in question, keeping only the rapid variations due to the musical rhythm.

This treatment according to the invention makes it possible to interpret, without a single error, pieces of a few minutes, with fine control at the same time of the speed and the volume of play, both when the sensors are placed on the player's hand or when they are located on the foot of a player who beats the measure with his foot. The device of the invention can be used as such, that is to say without any calibration, even magnetometers (it is actually working on signals cleared of continuous components). However, it may be advantageous to perform a calibration at the beginning of the game, which calibration can be repeated with each strike. It is then necessary to put in parallel the filtering having for object to free itself from the slow variations, and this calibration with each keystroke. In this case, it is no longer necessary to filter by the second filter. On the contrary, the fact of calibrating will ensure that in a position that is known to the user (at the moment of the striking), the magnetometer provides reference data thanks to the calibration. In a way, the data are realigned by these calibrations, whereas they were previously by the second filtering. One can also imagine to cumulate the second filtering and the calibration.

Moreover, all these treatments provide: a trigger signal that can be used to synchronize the play of a MIDI file, or to synchronize the scrolling of an MP3, WAV or WMA type audio file, according to an inventive method making the object of another patent application of the present applicants, having the title DEVICE AND METHOD FOR CONTROLLING THE SCROLL OF A FILE OF SIGNALS TO REPRODUCE; according to this method, the pre-recorded music file is marked with tags that indicate the timing elements to which a player will send synchronization strikes; a synchronization module then varies the speed of movement of the prerecorded audio file according to the variation of the rhythm of the player's strikes; an amplitude signal, which can be used to control the volume of a MIDI playback (usually in general, the velocity of the notes played) or the playback volume of an audio file.

Figure 6 shows a general flowchart of the treatments in one embodiment of the invention using only a gyrometer. For example, the AirMouse or GyroMouse of Movea (player 120B of FIG. 1) is used as input device. The processing carried out in the module 210 is comparable to the processing described above, except that we only use one sensor data item, which can be considered in an approximate manner that it is physically halfway between the accelerometer data. and the magnetometer data that provides absolute angles. The gyrometer is used here in the two detections: the one of the primary striking, with a treatment comparable to that of the accelerometer higher, except that the second filtering is not necessary, because a first filtering is already carried out in the AirMouse or the GyroMouse. Both filtering can however be cumulated. Crossings are detected here between the derivative of the signal coming from the AirMouse and this same filtered low pass signal recursively. The gesture power detection is also based on a measurement of the stroke between two successive primary keystrokes detected. This velocity calculation yields usable results, but is less effective than the two-mode approach. Because of the intermediate nature between measurements of an accelerometer and measurements of a magnetometer of the measurements of the gyrometer, it is sufficient for the two detections, but it is less effective also than the dedicated methods. This solution achieves a compromise that is not optimal but that can give other opportunities. On the one hand, the AirMouse is more accessible at least for the moment to the general public and is therefore of interest from this point of view even if we do not have the finesse of controlling the bimodality. In a way the Airmouse is between the Wii Music and a sensor providing two modes of motion capture. In addition, the mouse buttons provide complementary commands to, for example change a sound, or move to the next song, or to operate the pedal of a sampled piano for example.

The various embodiments of the invention may be improved by the variants set forth below.

An alternative embodiment consists in using two sensor modules in each of the player's hands, one of the modules being dedicated to the detection of primary keystrokes and the other to the measurement of velocity. It is also possible to exploit the other axes of the sensors to determine a heading information that allows to introduce a pan control and thus improve the centering to make detections completely independent of the player's positioning. Another alternative embodiment to improve the robustness 15 is to exploit the knowledge of the current musical content. We then introduce time windows deduced from current content in which a hit detected as primary is not taken into account because incoherent with said current content. In fact, this coherence will exploit a measure of the actual playing speed of the person (the time between the last two keystrokes) and compare it to the time elapsing between the two fragments contained in the module 220. differ too much (eg more than 25%) is that we record an acceleration (or deceleration) that seems excessive compared to what is played. It is deduced that there is a false detection. When such a false detection is identified, it is in fact still a strike devoid of musical meaning, which we deduce that it is an untimely detection. It is therefore purely and simply ignored (it does not trigger any multimedia fragment). Conversely, a non-detection can be simply remedied, the rhythmic elements of the piece being played by exploiting the last two hits detected. The examples described above are given by way of illustration of embodiments of the invention. They in no way limit the scope of the invention which is defined by the following claims.

Claims (15)

REVENDICATIONS1. Apparatus for interpreting gestures of a user comprising at least one measurement input module (10) comprising at least one motion sensor, a signal processing module (20) sampled at the output of the input module and a output module (30) adapted to reproduce the musical meaning of said gestures, said device being characterized in that the signal processing module (20) comprises a sub module for analysis and interpretation of gestures (210) comprising least one pair of two successive low-pass recursive filters adapted to receive at least one of the output signals of the module (10), a significant gesture detection function and a significant gesture detection confirmation function by comparing the variation between two successive values in the sample of at least one of the signals coming from the group of sensors with at least one chosen threshold value. 20 2. device for interpreting gestures according to claim 1 characterized in that the function of significant gestures detection is able to identify changes in sign between two successive values in the sample of the difference between at least one output of the first filter at least one of the filter pairs at the current value and at least one output of the second filter of the same pair of filters for the same signal at the previous value. 3. device for interpreting gestures according to claim 1 characterized in that the sub module for analyzing and interpreting gestures (210) further comprises a function for measuring the velocity of the gesture 30 detected at the output of the function detection confirmation. 4. device for interpreting gestures according to claim 3 characterized in that the velocity measurement function is able to calculate the stroke (Max-Min) between two significant gestures detected. 5. device for interpreting gestures according to claim 1 characterized in that the second filter is adapted to operate at a cutoff frequency lower than that of the first filter. 6. device for interpreting gestures according to claim 1 characterized in that the input module comprises at least a first accelerometer-type sensor and a second sensor selected from the group of sensors type magnetometer and gyrometer. 7. device for interpreting gestures according to claim 2 and claim 6 characterized in that the significant gestures detection function is adapted to receive at least one output of the second recursive filter of one of the pairs of filters applied to at least one of the signals of the first sensor. 8. Device for interpreting gestures according to claim 6, characterized in that the significant gesture detection confirmation function is able to receive at least one output of the second recursive filter of one of the pairs of filters applied to the input. least one of the signals of the second sensor. 9. Apparatus for interpreting gestures according to claim 8 characterized in that the selected threshold of the significant gesture detection confirmation function is of the order of 5/1000. 10. device for interpreting gestures according to claim 1 characterized in that the input module (10) transmits to the processing module (20) that signals from a sensor type gyrometer. 25 11. Device for interpreting gestures according to claim 3 characterized in that the input module (10) receives the signals of at least two sensors positioned on two independent parts of the body of the user, a first sensor providing via one of the pairs of recursive filters an input signal of the significant gesture detection function and a second sensor supplying via one of the recursive filter pairs an input signal of the gesture velocity measuring function detected at the output of the Significant gesture detection confirmation function. 12. Device for interpreting gestures according to claim 1, characterized in that the signal processing module (20) comprises a submodule (220) for input of pre-recorded multimedia contents. 13. Apparatus for interpreting gestures according to claim 12 characterized in that the sub-module (220) multimedia content input comprises a partitioning function of said multimedia content in time slots suitable for use in performing a second confirmation of detection of significant gestures detected. 14. Gesture interpreting device according to claim 1 characterized in that the input module (10) is adapted to transmit to the processing module (20) a signal representative of the position of the user in a substantially orthogonal plane to the direction of the significant gesture detected to make a second confirmation. 15. A method of interpreting significant gestures of a user comprising at least one measurement input step from at least one motion sensor, a step of processing sampled signals at the output of the step of input and an output step adapted to reproduce the musical meaning of said gestures, said method being characterized in that the signal processing step comprises a sub-step of gesture analysis and interpretation comprising at least one pair of two successive low pass recursive filtering of at least one of the signals, a significant gesture detection function and a significant gesture detection confirmation function by comparing the variation between two values in the sample of at least one signals from the sensor group with at least one selected threshold value.