Patent Description:
Spatial audio coding tools are well-known in the art and are standardized, for example, in the MPEG-surround standard. Spatial audio coding starts from a plurality of original input, e.g., five or seven input channels, which are identified by their placement in a reproduction setup, e.g., as a left channel, a center channel, a right channel, a left surround channel, a right surround channel and a low frequency enhancement channel. A spatial audio encoder may derive one or more downmix channels from the original channels and, additionally, may derive parametric data relating to spatial cues such as interchannel level differences in the channel coherence values, interchannel phase differences, interchannel time differences, etc. The one or more downmix channels are transmitted together with the parametric side information indicating the spatial cues to a spatial audio decoder for decoding the downmix channels and the associated parametric data in order to finally obtain output channels which are an approximated version of the original input channels. The placement of the channels in the output setup may be fixed, e.g., a <NUM> format, a <NUM> format, etc..

Also, spatial audio object coding tools are well-known in the art and are standardized, for example, in the MPEG SAOC standard (SAOC = spatial audio object coding). In contrast to spatial audio coding starting from original channels, spatial audio object coding starts from audio objects which are not automatically dedicated for a certain rendering reproduction setup. Rather, the placement of the audio objects in the reproduction scene is flexible and may be set by a user, e.g., by inputting certain rendering information into a spatial audio object coding decoder. Alternatively or additionally, rendering information may be transmitted as additional side information or metadata; rendering information may include information at which position in the reproduction setup a certain audio object is to be placed (e.g. over time). In order to obtain a certain data compression, a number of audio objects is encoded using an SAOC encoder which calculates, from the input objects, one or more transport channels by downmixing the objects in accordance with certain downmixing information. Furthermore, the SAOC encoder calculates parametric side information representing inter-object cues such as object level differences (OLD), object coherence values, etc. As in SAC (SAC = Spatial Audio Coding), the inter object parametric data is calculated for individual time/frequency tiles. For a certain frame (for example, <NUM> or <NUM> samples) of the audio signal a plurality of frequency bands (for example <NUM>, <NUM>, or <NUM> bands) are considered so that parametric data is provided for each frame and each frequency band. For example, when an audio piece has <NUM> frames and when each frame is subdivided into <NUM> frequency bands, the number of time/frequency tiles is <NUM>.

In 3D audio systems it may be desired to provide a spatial impression of an audio signal as if the audio signal is listened to in a specific room. In such a situation, a room impulse response of the specific room is provided, for example on the basis of a measurement thereof, and is used for processing the audio signal upon presenting it to a listener. It may be desired to process the direct sound and early reflections in such a presentation separated from the late reverberation. This requires to determine where the early reflections end and where the late reverberation starts.

<CIT> describes an apparatus for and method of externalizing a sound image output to headphones. The method includes localizing the sound image of an input signal to a predetermined area in front of a listener, and signal-processing a left signal component and a right signal component of the input signal with different delay values and gain values, respectively.

<CIT> describes a method and apparatus for processing sound sources to simulate environmental effects. Source channel blocks include direct, early reflection, and late reverberation blocks for conditioning the source feeds to include delays, spectral changes, and attenuations depending on the position, orientation and directivity of the sound sources, the position and orientation of the listener, and the position and sound transmission and reflection properties of obstacles and walls in a modeled environment. The outputs of the source channel blocks are combined and provided to single reverberation block generating both the early reflections and the late reverberation for all sound sources.

<CIT> describes a method of processing a series of input audio signals representing a series of virtual audio sound sources placed at predetermined positions around a listener to produce a reduced set of audio output signals for playback over speaker devices placed around a listener. The method includes (a) for each of the input audio signals and for each of the audio output signals: (i) convolving the input audio signals with an initial head portion of a corresponding impulse response mapping substantially the initial sound and early reflections for an impulse response of a corresponding virtual audio source to a corresponding speaker device so as to form a series of initial responses, (b) for each of the input audio signals and for each of the audio output signals: (i) forming a combined mix from the audio input signals; (ii) forming a combined convolution tail from the tails of the corresponding impulse responses, (iii) convolving the combined mix with the combined convolution tail to form a combined tail response; and (c) for each of the audio output signals: (i) combining a corresponding series of initial responses and a corresponding combined tail response to form the audio output signal.

<CIT> describes a method for modeling a room impulse response which includes receiving a sound pressure signal that is obtained by a microphone when an impulse-typed sound source is excited and detecting a room impulse response; determining boundaries between a plurality of intervals of the room impulse response such that the room impulse response is divided into the plurality of intervals on a time domain; and modeling the room impulse response using a different modeling method for each of the plurality of divided intervals.

It is an object of the present invention to provide an improved approach for processing an audio signal in accordance with a room impulse response.

This object is achieved by a method of claim <NUM>, a signal processing unit of claim <NUM>, an audio encoder of claim <NUM>, an audio decoder of claim <NUM>, and a binaural renderer of claim <NUM>.

The present invention is based on the inventor's findings that in conventional approaches a problem exists in that there are situations where the determination of the transition from early reflections to late reverberation is too early because a correlation used for judging the occurrence of the transition already reaches a threshold before the first reflection even occurred or impinged. On the basis of these findings and since it is known that the transition time must be larger than the arrival time of the first reflection, because the first reflection is clearly distinct and can for sure not be the late diffuse reverberation, the inventors found that it is necessary to avoid the use of a fixed threshold, rather, in accordance with the inventive approach the threshold is defined such that it is dependent on the correlation at the impinging time of one of the early reflections. This assures that the first reflection is always located before the transition time.

Embodiments of the present invention will be described with regard to the accompanying drawings, in which:.

Embodiments of the inventive approach for processing an audio signal in accordance with a room impulse response and for determining in a room impulse response a transition from early reflections to late reverberation will be described. The following description will start with a system overview of a 3D audio codec system in which the inventive approach may be implemented.

<FIG> and <FIG> show the algorithmic blocks of a 3D audio system in accordance with embodiments. More specifically, <FIG> shows an overview of a 3D audio encoder <NUM>. The audio encoder <NUM> receives at a pre-renderer/mixer circuit <NUM>, which may be optionally provided, input signals, more specifically a plurality of input channels providing to the audio encoder <NUM> a plurality of channel signals <NUM>, a plurality of object signals <NUM> and corresponding object metadata <NUM>. The object signals <NUM> processed by the pre-renderer/mixer <NUM> (see signals <NUM>) may be provided to a SAOC encoder <NUM> (SAOC = Spatial Audio Object Coding). The SAOC encoder <NUM> generates the SAOC transport channels <NUM> provided to an USAC encoder <NUM> (USAC = Unified Speech and Audio Coding). In addition, the signal SAOC-SI <NUM> (SAOC-SI = SAOC side information) is also provided to the USAC encoder <NUM>. The USAC encoder <NUM> further receives object signals <NUM> directly from the pre-renderer/mixer as well as the channel signals and pre-rendered object signals <NUM>. The object metadata information <NUM> is applied to a OAM encoder <NUM> (OAM = object metadata) providing the compressed object metadata information <NUM> to the USAC encoder. The USAC encoder <NUM>, on the basis of the above mentioned input signals, generates a compressed output signal mp4, as is shown at <NUM>.

<FIG> shows an overview of a 3D audio decoder <NUM> of the 3D audio system. The encoded signal <NUM> (mp4) generated by the audio encoder <NUM> of <FIG> is received at the audio decoder <NUM>, more specifically at an USAC decoder <NUM>. The USAC decoder <NUM> decodes the received signal <NUM> into the channel signals <NUM>, the pre-rendered object signals <NUM>, the object signals <NUM>, and the SAOC transport channel signals <NUM>. Further, the compressed object metadata information <NUM> and the signal SAOC-SI <NUM> is output by the USAC decoder <NUM>. The object signals <NUM> are provided to an object renderer <NUM> outputting the rendered object signals <NUM>. The SAOC transport channel signals <NUM> are supplied to the SAOC decoder <NUM> outputting the rendered object signals <NUM>. The compressed object meta information <NUM> is supplied to the OAM decoder <NUM> outputting respective control signals to the object renderer <NUM> and the SAOC decoder <NUM> for generating the rendered object signals <NUM> and the rendered object signals <NUM>. The decoder further comprises a mixer <NUM> receiving, as shown in <FIG>, the input signals <NUM>, <NUM>, <NUM> and <NUM> for outputting the channel signals <NUM>. The channel signals can be directly output to a loudspeaker, e.g., a <NUM> channel loudspeaker, as is indicated at <NUM>. The signals <NUM> may be provided to a format conversion circuit <NUM> receiving as a control input a reproduction layout signal indicating the way the channel signals <NUM> are to be converted. In the embodiment depicted in <FIG>, it is assumed that the conversion is to be done in such a way that the signals can be provided to a <NUM> speaker system as is indicated at <NUM>. Also, the channel signals <NUM> may be provided to a binaural renderer <NUM> generating two output signals, for example for a headphone, as is indicated at <NUM>.

In an embodiment of the present invention, the encoding/decoding system depicted in <FIG> and <FIG> is based on the MPEG-D USAC codec for coding of channel and object signals (see signals <NUM> and <NUM>). To increase the efficiency for coding a large amount of objects, the MPEG SAOC technology may be used. Three types of renderers may perform the tasks of rendering objects to channels, rendering channels to headphones or rendering channels to a different loudspeaker setup (see <FIG>, reference signs <NUM>, <NUM> and <NUM>). When object signals are explicitly transmitted or parametrically encoded using SAOC, the corresponding object metadata information <NUM> is compressed (see signal <NUM>) and multiplexed into the 3D audio bitstream <NUM>.

The algorithm blocks of the overall 3D audio system shown in <FIG> and <FIG> will be described in further detail below.

The pre-renderer/mixer <NUM> may be optionally provided to convert a channel plus object input scene into a channel scene before encoding. Functionally, it is identical to the object renderer/mixer that will be described below. Pre-rendering of objects may be desired to ensure a deterministic signal entropy at the encoder input that is basically independent of the number of simultaneously active object signals. With pre-rendering of objects, no object metadata transmission is required. Discrete object signals are rendered to the channel layout that the encoder is configured to use. The weights of the objects for each channel are obtained from the associated object metadata (OAM).

The USAC encoder <NUM> is the core codec for loudspeaker-channel signals, discrete object signals, object downmix signals and pre-rendered signals. It is based on the MPEG-D USAC technology. It handles the coding of the above signals by creating channel-and object mapping information based on the geometric and semantic information of the input channel and object assignment. This mapping information describes how input channels and objects are mapped to USAC-channel elements, like channel pair elements (CPEs), single channel elements (SCEs), low frequency effects (LFEs) and quad channel elements (QCEs) and CPEs, SCEs and LFEs, and the corresponding information is transmitted to the decoder. All additional payloads like SAOC data <NUM>, <NUM> or object metadata <NUM> are considered in the encoder's rate control. The coding of objects is possible in different ways, depending on the rate/distortion requirements and the interactivity requirements for the renderer. In accordance with embodiments, the following object coding variants are possible:.

The SAOC encoder <NUM> and the SAOC decoder <NUM> for object signals may be based on the MPEG SAOC technology. The system is capable of recreating, modifying and rendering a number of audio objects based on a smaller number of transmitted channels and additional parametric data, such as OLDs, IOCs (Inter Object Coherence), DMGs (DownMix Gains). The additional parametric data exhibits a significantly lower data rate than required for transmitting all objects individually, making the coding very efficient. The SAOC encoder <NUM> takes as input the object/channel signals as monophonic waveforms and outputs the parametric information (which is packed into the 3D-Audio bitstream <NUM>) and the SAOC transport channels (which are encoded using single channel elements and are transmitted). The SAOC decoder <NUM> reconstructs the object/channel signals from the decoded SAOC transport channels <NUM> and the parametric information <NUM>, and generates the output audio scene based on the reproduction layout, the decompressed object metadata information and optionally on the basis of the user interaction information.

The object metadata codec (see OAM encoder <NUM> and OAM decoder <NUM>) is provided so that, for each object, the associated metadata that specifies the geometrical position and volume of the objects in the 3D space is efficiently coded by quantization of the object properties in time and space. The compressed object metadata cOAM <NUM> is transmitted to the receiver <NUM> as side information.

The object renderer <NUM> utilizes the compressed object metadata to generate object waveforms according to the given reproduction format. Each object is rendered to a certain output channel according to its metadata. The output of this block results from the sum of the partial results. If both channel based content as well as discrete/parametric objects are decoded, the channel based waveforms and the rendered object waveforms are mixed by the mixer <NUM> before outputting the resulting waveforms <NUM> or before feeding them to a postprocessor module like the binaural renderer <NUM> or the loudspeaker renderer module <NUM>.

The binaural renderer module <NUM> produces a binaural downmix of the multichannel audio material such that each input channel is represented by a virtual sound source. The processing is conducted frame-wise in the QMF (Quadrature Mirror Filterbank) domain, and the binauralization is based on measured binaural room impulse responses.

The loudspeaker renderer <NUM> converts between the transmitted channel configuration <NUM> and the desired reproduction format. It may also be called "format converter". The format converter performs conversions to lower numbers of output channels, i.e., it creates downmixes.

<FIG> shows an example for implementing a format converter <NUM>. The format converter <NUM>, also referred to as loudspeaker renderer, converts between the transmitter channel configuration and the desired reproduction format. The format converter <NUM> performs conversions to a lower number of output channels, i.e., it performs a downmix (DMX) process <NUM>. The downmixer <NUM>, which preferably operates in the QMF domain, receives the mixer output signals <NUM> and outputs the loudspeaker signals <NUM>. A configurator <NUM>, also referred to as controller, may be provided which receives, as a control input, a signal <NUM> indicative of the mixer output layout, i.e., the layout for which data represented by the mixer output signal <NUM> is determined, and the signal <NUM> indicative of the desired reproduction layout. Based on this information, the controller <NUM>, preferably automatically, generates optimized downmix matrices for the given combination of input and output formats and applies these matrices to the downmixer <NUM>. The format converter <NUM> allows for standard loudspeaker configurations as well as for random configurations with non-standard loudspeaker positions.

<FIG> illustrates an embodiment of the binaural renderer <NUM> of <FIG>. The binaural renderer module may provide a binaural downmix of the multichannel audio material. The binauralization may be based on a measured binaural room impulse response. The room impulse response may be considered a "fingerprint" of the acoustic properties of a real room. The room impulse response is measured and stored, and arbitrary acoustical signals can be provided with this "fingerprint", thereby allowing at the listener a simulation of the acoustic properties of the room associated with the room impulse response. The binaural renderer <NUM> may be programmed or configured for rendering the output channels into two binaural channels using head related transfer functions or binaural room impulse responses (BRIR). For example, for mobile devices binaural rendering is desired for headphones or loudspeakers attached to such mobile devices. In such mobile devices, due to constraints it may be necessary to limit the decoder and rendering complexity. In addition to omitting decorrelation in such processing scenarios, it may be preferred to first perform a downmix using a downmixer <NUM> to an intermediate downmix signal <NUM>, i.e., to a lower number of output channels which results in a lower number of input channel for the actual binaural converter <NUM>. For example, a <NUM> channel material may be downmixed by the downmixer <NUM> to a <NUM> intermediate downmix or, alternatively, the intermediate downmix may be directly calculated by the SAOC decoder <NUM> in <FIG> in a kind of a "shortcut" mode. The binaural rendering then only has to apply ten HRTFs (Head Related Transfer Functions) or BRIR functions for rendering the five individual channels at different positions in contrast to applying <NUM> HRTF or BRIR functions if the <NUM> input channels were to be directly rendered. The convolution operations necessary for the binaural rendering require a lot of processing power and, therefore, reducing this processing power while still obtaining an acceptable audio quality is particularly useful for mobile devices. The binaural renderer <NUM> produces a binaural downmix <NUM> of the multichannel audio material <NUM>, such that each input channel (excluding the LFE channels) is represented by a virtual sound source. The processing may be conducted frame-wise in QMF domain. The binauralization is based on measured binaural room impulse responses, and the direct sound and early reflections may be imprinted to the audio material via a convolutional approach in a pseudo-FFT domain using a fast convolution on-top of the QMF domain, while late reverberation may be processed separately.

<FIG> shows an example of a room impulse response h(t) <NUM>. The room impulse response comprises three components, the direct sound <NUM>, early reflections <NUM> and late reverberation <NUM>. Thus, the room impulse response describes the reflection behavior of an enclosed reverberant acoustic space when an impulse is played. The early reflections <NUM> are discrete reflections with increasing density, and the part of the impulse response where the individual reflections can no longer be discriminated is called late reverberation <NUM>. The direct sound <NUM> can be easily identified in the room impulse response and can be separated from early reflections, however, the transition from the early reflection <NUM> to late reverberation <NUM> is less obvious.

In the following embodiments of the inventive approach will be described in further detail. In accordance with embodiments of the invention, an audio signal is separately processed with an early part and a late reverberation of a room impulse response. The audio signal processed with the early part of the room impulse response and the reverberated signal are combined and output as the output audio signal. For the separate processing the transition in the room impulse response from the early part to the late reverberation needs to be known. The transition is determined by a correlation measure that reaches a threshold, wherein the threshold is set dependent on the correlation measure for a selected one of the early reflections in the early part of the room impulse response. The correlation measure may describe with regard to the room impulse response the similarity of the decay in acoustic energy including the initial state and the decay in acoustic energy starting at any time following the initial state over a predefined frequency range.

In accordance with embodiments, the separate processing of the audio signal comprises processing the audio signal with the early reflection part <NUM>, <NUM> of the room impulse response during a first process, and processing the audio signal with the diffuse reverberation <NUM> of the room impulse response during a second process that is different and separate from the first process. Changing from the first process to the second process occurs at the transition time. In accordance with further embodiments, in the second process the diffuse (late) reverberation <NUM> may be replaced by a synthetic reverberation. In this case the room impulse response provided may contain only the early reflection part <NUM>, <NUM> (see <FIG>) and the late diffuse reverberation <NUM> is not included.

<FIG> shows a block diagram illustrating a first exemplary signal processing unit for separately processing an audio signal with an early part and a late reverberation of the room impulse in accordance with an embodiment of the invention. The processing of the audio signal in accordance with different parts of the room impulse response may be carried out in a binaural renderer <NUM> that has been described above. The audio input signal <NUM> may be a non-reverberant audio material, e.g. a multichannel audio input signal, that is convolved with the room impulse response, for example a room impulse response measured using an artificial head or in-ear microphones. This convolution allows to gain a spatial impression of the original non-reverberant audio material as if the audio material is listened to in the room associated with room impulse response. For example, in the above mentioned binaural renderer <NUM>, it may be desired to process the audio signal with the direct sound <NUM> and the early reflection <NUM> in the room impulse response and to process the audio signal with the late reverberation <NUM> separately. For processing the audio input signal <NUM>, a block <NUM> for direct sound processing, a block <NUM> for early reflections processing and a block <NUM> for late reverberation processing are provided. The output signals <NUM> and <NUM> of the respective blocks <NUM> to <NUM> are combined by a first adder <NUM> for generating an early processed signal <NUM>. The early processed signal <NUM> and the reverberated signal <NUM> provided by processor <NUM> are combined by a second adder <NUM> for generating the audio output signal <NUM> which provides to a listener the impression as if the audio signal is listened to in the room associated with the room impulse responses.

Processing the late reverberation <NUM> separate from the direct sound and early reflections is advantageous due to the reduced computational complexity. More specifically, using a convolution for the entire impulse response is computationally very costly. Therefore, reverberation algorithms with lower complexity are typically used to process audio signals in order to simulate late reverberation. The direct sound and early reflections part of the impulse response are computed more accurately, for example by a convolution. A further advantage is the possibility of reverberation control. This allows the late reverberation to be modified dependent, for example, on a user input, a measured room parameter or dependent on the contents of the audio signal. To achieve the above advantages the transition (e.g., the point in time) where the early reflections <NUM> end and where the late reverberation <NUM> starts needs to be known. When the late reverberation processing starts too early, the audio signal may be of lower quality as the human hearing can detect the missing distinct early reflections. On the other hand, if the transition time is detected too late, the computational efficiency will not be exploited, as the early reflections processing is typically more costly than the late reverberation processing. The transition, e.g., in time domain samples, may be fed to the binaural renderer as an input parameter which will then, dependent on the received transition, control the processors <NUM> to <NUM> for separately processing the audio signal.

<FIG> illustrates a block diagram of another exemplary signal processing unit for separately processing an audio signal with an early part and a late reverberation of the room impulse in accordance with another embodiment of the invention. The input signal <NUM>, for example a multichannel audio input signal, is received and applied to a first processor <NUM> for processing the early part, namely for processing the audio signal in accordance with the direct sound <NUM> and the early reflections <NUM> in the room impulse response <NUM> shown in <FIG>. The multichannel audio input signal <NUM> is also applied to a second processor <NUM> for processing the audio signal in accordance with the late reverberation <NUM> of the room impulse response. In a binaural renderer, as mentioned above, it may be desired to process the direct sound and early reflections separate from the late reverberation, mainly because of the reduced computational complexity. The processing of the direct sound and early reflections may, for example, be imprinted to the audio signal by a convolutional approach carried out by the first processor <NUM>, while the late reverberation may be replaced by a synthetic reverberation provided by the second processor <NUM>. The overall binaural output signal <NUM> is then a combination of the convolutional result <NUM> provided by the processor <NUM> and the synthetic reverberated signal <NUM> provided by the processor <NUM>. In accordance with embodiments the signals <NUM> and <NUM> are combined by an adder <NUM> outputting the overall binaural output signal <NUM>.

As mentioned, the first processor <NUM> may cause a convolution of the audio input signal <NUM> with a direct sound and early reflections of the room impulse response that may be provided to the first processor <NUM> from an external database <NUM> holding a plurality of recorded binaural room impulse responses. The second processor or reverberator <NUM> may operate on the basis of reverberator parameters, like the reverberation RT60 and the reverberation energy, that may be obtained from the stored binaural room impulse responses by an analysis <NUM>. It is noted that the analysis <NUM> is not necessarily part of the renderer, rather this is to indicate that from the respective responses stored in database <NUM> the respective reverberation parameters may be derived; this may be done externally. The reverberator parameters may be determined, for example, by calculating the energy and the RT60 reverberation time in an octave or one-third octave filterbank analysis, or may be mean values of the results of multiple impulse response analyses.

In addition, both processors <NUM> and <NUM> receive from the database <NUM> - directly or via the analysis <NUM> - as input parameter also information about the transition in the room impulse response from the early part to the late reverberation. The transition may be determined in a way as will be described in further detail below.

In accordance with embodiments, the transition analysis may be used to separate the early reflections and the late reverberation. It may be fed to the binaural renderer as an input parameter (e.g., it may be read from a dedicated file / interface along with RT60-values and energy values that are used to configure the reverberator). The analysis may be based on one set of binaural room impulse responses (a set of BRIR pairs for a multitude of azimuth and elevation angles). The analysis may be a preprocessing step that is carried out separately for every impulse response and then the median of all transition values is taken as an overall transition value of the one BRIR set. This overall transition value may then be used to separate the early reflections from the late reverberation in the calculation of the binaural output signal.

Several approaches for determining the transition are known, however, these approaches are disadvantages as will be described now. In prior art reference [<NUM>] a method is described which uses the energy decay relief (EDR) and a correlation measure to determine the transition time from early reflections to late reverberation. However, the approach described in prior art reference [<NUM>] is disadvantageous.

Another known approach is to describe early reflections by the dispersion of echoes in a space, for example by the average number of reflections per second, and to determine the beginning of the late reverberation when this number exceeds a predefined threshold (see prior art reference [<NUM>]). This approach relies on the room characteristic, namely the room volume, which is often unknown. The room volume cannot be easily extracted from a measured impulse response. Therefore, this method is not applicable for the calculation of the transition from measured impulse responses. Also, there is no common knowledge how dense the reflections have to be to be called late reverberation.

Another possibility, described in prior art reference [<NUM>], is to compare the actual distribution at a time in an impulse response window to a Gaussian distribution in the time domain. The late reverberation is assumed to have a normal distribution. In a normal distribution approximately one third (exactly <NUM>/e) of the samples lie outside one standard deviation of the mean and two thirds of the samples are within one standard deviation of the mean. Distinct early reflections have more samples within one standard deviation and fewer outside. The ratio of samples outside one standard deviation versus the samples inside one standard deviation may be used to define the transition time. However, the disadvantage of this approach is that the transition is difficult to define with this measure, because the ratio sometimes fluctuates around the threshold. The measure is also strongly dependent on the size and the type of the sliding window in which the ratio is calculated.

Besides the above mentioned approaches, also the Kurtosis (the higher order cumulant of a stochastic signal) may be used to determine the transition time. It rapidly decreases when approaching towards the late part of the impulse response, as is outlined in prior art reference [<NUM>]. However, the definition of the threshold for the transition (either use of a rapid decrease or the time when it first reaches zero) is not clear.

There is yet another approach that does not rely on the analysis of a measured impulse response, but on the room volume, as is described in [<NUM>]. This approach assumes that the transition time is only dependent on the volume, but it does not take into account the diffusing properties of the boundaries. Therefore, the result can only be an approximation of the transition time and is not as accurate as needed for avoiding the above mentioned disadvantages when not precisely determining the transition time. Further, the volume of a room is often not known and cannot be easily extracted from a measured impulse response.

Other known approaches completely disregard the environment and define the transition time to be simply <NUM>, see for example in prior art reference [<NUM>]. This number, however, is totally detached from the room characteristics or a measured impulse response and, therefore, is much too inaccurate for the purpose of separating late reverberation from the reminder of the impulse response.

The present invention, in accordance with embodiments, provides in addition to the improved audio signal processing also an improved approach for determining the transition time between early reflections and late reverberation in a room impulse response yielding a more accurate determination of the transition time. Embodiments, as will be described below, provide a simple and effective possibility to calculate the transition time from a measured impulse response using an FFT analysis.

<FIG> shows a flow diagram of an approach for determining a transition time between early reflections and late reverberation in a room impulse response in accordance with an embodiment of the invention. To determine the transition time from early reflections to late reverberation, in a first step <NUM> a time-frequency distribution of the acoustic energy is determined. For example, in accordance with embodiments the energy decay relief (E(t,f), EDR) may be calculated in step <NUM>. The EDR can be directly calculated from a measured (e.g., binaural) room impulse response and may be interpreted as a frequencydomain expansion of the commonly used energy decay curve (Schroeder integration, EDC (d)) that shows the remaining energy in the impulse response after a time t. Instead of using the broadband impulse response, the EDR is derived from a time-frequency representation and many different time-frequency representations may be used for this purpose. Once the time-frequency distribution of the acoustic energy has been determined in step <NUM>, in step <NUM> a correlation measure between the acoustic energy at a time block of the time-frequency distribution and the overall acoustic energy at an initial state is determined. In step <NUM> it is determined as to whether the correlation measure reaches a defined threshold (e.g., falls below the defined threshold) or not. If it does not reach the threshold, the method proceeds to step <NUM> where the next time block and the distribution following the current time block is selected and steps <NUM> and <NUM> are repeated for the next time block. Thus, in accordance with steps <NUM> to <NUM> a correlation measure is used to calculate the correlation value between each time block of the EDR determined in step <NUM> with the overall energy at the initial state. The transition time is reached when the correlation measure reaches the defined threshold (e.g., falls below the defined threshold). In other words, when it is determined in step <NUM> that for a current time block the correlation measure is lower than the threshold, the method proceeds to step <NUM> where the time of the current time block is output as the transition time.

In the following, an embodiment of the inventive approach will be described in further detail. Initially, a measured binaural impulse response may be taken as an input for the calculation of the transition time. Then, a Page or Levin distribution is employed for the calculation of the energy decay relief (EDR). The Page distribution refers to the derivative of the past running spectrum and the Page distribution of the time-reverse signal is called the Levin distribution (see also prior art reference [<NUM>]). This distribution describes an instantaneous power spectrum, and the EDR of the impulse response h(t) (see, for example, <FIG>) is calculated as follows: <MAT> where.

The calculation in accordance with the above equation starts at the direct sound <NUM> (see <FIG>), and with increasing time the energy decay relief contains less distinct reflections and more stochastic reverberation. In accordance with the described embodiment, the energy decay relief is calculated for time blocks having a length of <NUM> for ease of computation. By means of the above described functionality, the time-frequency distribution of the acoustic energy is determined as has been described with regard to step <NUM> in <FIG>.

Following this, as has been described with regard to steps <NUM> to <NUM> in <FIG>, the correlation measure p(t) that is based on the Pearson's Product-Moment Correlation (also known as correlation coefficient) is determined. More specifically, the correlation of the acoustic energy for each time block with the overall energy at the initial state is determined, in accordance with embodiments, as follows: <MAT> where.

The above correlation describes the similarity of the decay including the initial state and the decay starting at any time t. It is calculated from the broadband EDR, using the full frequency range of the EDR for the calculation, thereby comparing the complete initial energetic situation with the situation at the time t.

The present invention is not limited to the calculation of the correlation over all frequencies. Rather, the correlation may also be calculated over a predefined frequency range. The frequency range may be determined from the audio signal to be processed.

For example, for specific audio signals the frequency range may be limited to a predefined range, e.g., the range of audible frequencies. In accordance with embodiments, the frequency range may be <NUM> to <NUM>. It is noted that other ranges may also be selected, e.g. by empirical studies.

In accordance with an embodiment, an effective FFT-based implementation of the EDR may be used. A window having an effective length of the measured impulse response is applied, and it is assumed that a measured impulse response has an effective length of <NUM><NUM> which is equal to <NUM> frequency bins. During the calculation, this window is shifted by the discrete length of a single time block, and the end of the window is zero-padded. In accordance with embodiments a time block length of <NUM> is used, and for a simple and effective calculation of the EDR the following approach is applied:.

The above approach is advantageous, as no additional filter bank or the like is required for the narrow band calculation of the EDR; only a shifting of the window is required. <FIG> shows an example for an energy decay relief achieved for an impulse response in accordance with the above described FFT-based approach.

As has been described in <FIG> with regard to steps <NUM> and <NUM>, the correlation determined in the above described way will then be compared to a predefined threshold. The smaller the threshold is, the more the transition time moves towards the end of the impulse response. For example, for binaural impulse responses, if the threshold is chosen to be <NUM>/e ≈ <NUM> (see also prior art reference [<NUM>]), the transition is too early at some azimuthal angles, because the correlation falls below the threshold already before the first reflection occurred or impinged. However, since it is known that the transition time must be later than the arrival time of the first reflection, because the first reflection is clearly distinct and can for sure not be the late diffuse reverberation, in accordance with embodiments, the threshold is not defined as a fixed threshold. Rather, in accordance with the inventive approach the threshold is defined such that it is dependent on the correlation at the impinging time of the first reflection. With this definition, it is assured that the first reflection is always located before the transition time. In accordance with embodiments, the transition time, as shown in step <NUM>, is considered to be reached when the following applies: <MAT> where.

In accordance with embodiments, the constant value may be <MAT>, however, the present invention is not limited to this value. In accordance with embodiments the constant value may be approximated by <MAT>, e.g. by rounding or truncating <MAT> with respect to a predefined decimal place (see below).

In the described embodiment, tF is the time block index where the first reflection after the direct sound impinges.

<FIG> depicts the transition time determination in accordance with the inventive approach where the threshold is calculated dependent on the impulse response by multiplication of the correlation at the impinging point of the first reflection and a fixed or constant value of <NUM>/e. The amplitude of the room impulse response <NUM> is shown over the number of samples, and a first reflection <NUM> is also indicated. The waveform <NUM> indicates the correlation values obtained by applying equation (<NUM>). At <NUM> the correlation value at the first reflection is shown which, in the example depicted has a value of <NUM>. Also, the conventionally used fixed threshold of <NUM>/e is shown at <NUM>. The correlation value <NUM> for the first reflection and the original fixed value <NUM>/e are applied to a multiplier <NUM> which generates the new threshold that is dependent on the correlation value at the first reflection and, in the described embodiment has a value of <NUM> as is shown at <NUM>. Thus, when compared to conventional approaches, the transition point <NUM> is moved further towards the right so that all samples following the transition point <NUM> are now considered late reverberation <NUM> and all samples before are considered early reflection <NUM>. It can be seen that the resulting decision time <NUM> is more robust. For example, in a binaural room impulse response this means that the calculated transition time is much more stable over the azimuthal angle. This can be seen from a comparison of <FIG> and <FIG>. <FIG> shows the transition times when applying the approach described in prior art reference [<NUM>] for the left channel <NUM> and the right channel <NUM> for a measured binaural room impulse response using the above described EDC implementation but with a fixed threshold of <NUM>/e. A dependency on the ear and the azimuthal angle is clearly visible as well as the deep dips in the transition time down to less than <NUM> that are due to the fact that the correlation ρ(t) falls below the threshold before the first reflection impinges. <FIG> shows the transition time for the left channel <NUM> and the right channel <NUM> when calculated in accordance with the inventive approach. It can be seen that the resulting transition time is much less dependent on the ear and the azimuthal angle when compared to the conventional approach explained with regard to <FIG>.

In accordance with embodiments, the transition time is considered to be reached when the correlation falls below or is equal to the threshold value for the first time and does not increase again over the threshold afterwards. The time value that is associated with this sample in the calculated correlation function is the time where the late reverberation of the impulse response is considered to start. In accordance with the inventive approach, the impinging time of the first reflection may be determined by a running kurtosis operator, as is described in prior art reference [<NUM>]. Alternatively, the first reflection may be detected by other methods, for example, by a threshold detection or by an attack detection as it is, for example, described in prior art reference [<NUM>].

In accordance with embodiments, e-<NUM> = <NUM> is used as a value to indicate a low correlation in stochastic processes as is, for example, indicated also in prior art reference [<NUM>]. In accordance with embodiments, this value is used with four decimal digits such that e-<NUM> is approximated as <NUM>. In accordance with other embodiments also more or less decimal digits may be used and it has been observed that the detected transition time changes accordingly with the deviation from the exact number of e-<NUM>. For example, when using value of <NUM> this results only in minimal changes in the transition time of below <NUM>.

In accordance with further embodiments, the impulse response may be band-limited, and in this case, the EDR may be calculated over a limited frequency range and also the correlation may be calculated over the limited frequency range of the EDR. Alternative frequency transforms or filter banks may also be used, for example, approaches operating completely in the FFT domain, thereby saving additional transforms, for example when using FFT based filtering/convolution.

It is noted that in the above description of the embodiments reference has been made to a value of the correlation value for the first reflection. However, other embodiments may use a correlation value calculated for another one of the early reflections.

As mentioned above, the inventive approach, in accordance with embodiments may be used in a binaural processor for binaural processing of audio signals. In the following an embodiment of binaural processing of audio signals will be described. The binaural processing may be carried out as a decoder process converting the decoded signal into a binaural downmix signal that provides a surround sound experience when listened to over headphones.

<FIG> shows a schematic representation of a binaural renderer <NUM> for binaural processing of audio signals in accordance with an embodiment of the present invention. <FIG> also provides an overview of the QMF domain processing in the binaural renderer. At an input <NUM> the binaural renderer <NUM> receives the audio signal to be processed, e.g., an input signal including N channels and <NUM> QMF bands. In addition the binaural renderer <NUM> receives a number of input parameters for controlling the processing of the audio signal. The input parameters include the binaural room impulse response (BRIR) <NUM> for 2xN channels and <NUM> QMF bands, an indication Kmax <NUM> of the maximum band that is used for the convolution of the audio input signal with the early reflection part of the BRIRs <NUM>, and the reverberator parameters <NUM> and <NUM> mentioned above (RT60 and the reverberation energy). The binaural renderer <NUM> comprises a fast convolution processor <NUM> for processing the input audio signal <NUM> with the early part of the received BRIRs <NUM>. The processor <NUM> generates at an output the early processed signal <NUM> including two channels and Kmax QMF bands. The binaural renderer <NUM> comprises, besides the early processing branch having the fast convolution processor <NUM>, also a reverberation branch including two reverberators 816a and 816b each receiving as input parameter the RT60 information <NUM> and the reverberation energy information <NUM>. The reverberation branch further includes a stereo downmix processor <NUM> and a correlation analysis processor <NUM> both also receiving the input audio signal <NUM>. In addition, two gain stages 821a and 821b are provided between the stereo downmix processor <NUM> and the respective reverberators 816a and 816b for controlling the gain of a downmixed signal <NUM> provided by the stereo downmix processor <NUM>. The stereo downmix processor <NUM> provides on the basis of the input signal <NUM> the downmixed signal <NUM> having two bands and <NUM> QMF bands. The gain of the gain stages 821a and 821b is controlled by a respective control signals 824a and 824b provided by the correlation analysis processor <NUM>. The gain controlled downmixed signal is input into the respective reverberators 816a and 816b generating respective reverberated signals 826a, 826b. The early processed signal <NUM> and the reverberated signals 826a, 826b are received by a mixer <NUM> that combines the received signals into the output audio signal <NUM> having two channels and <NUM> QMF bands. In addition, in accordance with the present invention, the fast convolution processor <NUM> and the reverberators 816a and 816b receive an additional input parameter <NUM> indicating the transition in the room impulse response <NUM> from the early part to the late reverberation determined as discussed above.

The binaural renderer module <NUM> (e.g., the binaural renderer <NUM> of <FIG> or <FIG>) has as input <NUM> the decoded data stream. The signal is processed by a QMF analysis filterbank as outlined in ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. <NUM> with the modifications stated in ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. The renderer module <NUM> may also process QMF domain input data; in this case the analysis filterbank may be omitted. The binaural room impulse responses (BRIRs) <NUM> are represented as complex QMF domain filters. The conversion from time domain binaural room impulse responses to the complex QMF filter representation is outlined in ISO/IEC FDIS <NUM>-<NUM>:<NUM>, Annex B. The BRIRs <NUM> are limited to a certain number of time slots in the complex QMF domain, such that they contain only the early reflection part <NUM>, <NUM> (see <FIG>) and the late diffuse reverberation <NUM> is not included. The transition point <NUM> from early reflections to late reverberation is determined as described above, e.g., by an analysis of the BRIRs <NUM> in a preprocessing step of the binaural processing. The QMF domain audio signals <NUM> and the QMF domain BRIRs <NUM> are then processed by a bandwise fast convolution <NUM> to perform the binaural processing. A QMF domain reverberator 816a, 816b is used to generate a <NUM>-channel QMF domain late reverberation 826a, 826b. The reverberation module 816a, 816b uses a set of frequency-dependent reverberation times <NUM> and energy values <NUM> to adapt the characteristics of the reverberation. The waveform of the reverberation is based on a stereo downmix <NUM> of the audio input signal <NUM> and it is adaptively scaled 821a, 821b in amplitude depending on a correlational analysis <NUM> of the multi-channel audio signal <NUM>. The <NUM>-channel QMF domain convolutional result <NUM> and the <NUM>-channel QMF domain reverberation 816a, 816b are then combined <NUM> and finally, two QMF synthesis filter banks compute the binaural time domain output signals <NUM> as outlined in ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. The renderer can also produce QMF domain output data; the synthesis filterbank is then omitted.

Audio signals <NUM> that are fed into the binaural renderer module <NUM> are referred to as input signals in the following. Audio signals <NUM> that are the result of the binaural processing are referred to as output signals. The input signals <NUM> of the binaural renderer module <NUM> are audio output signals of the core decoder (see for example signals <NUM> in <FIG>). The following variable definitions are used:.

The processing of the input signal is now described. The binaural renderer module operates on contiguous, non-overlapping frames of length L = <NUM> time domain samples of the input audio signals and outputs one frame of L samples per processed input frame of length L.

The initialization of the binaural processing block is carried out before the processing of the audio samples delivered by the core decoder (see for example the decoder of <NUM> in <FIG>) takes place. The initialization consists of several processing steps.

The reverberator module 816a, 816b takes a frequency-dependent set of reverberation times <NUM> and energy values <NUM> as input parameters. These values are read from an interface at the initialization of the binaural processing module <NUM>. In addition the transition time <NUM> from early reflections to late reverberation in time domain samples is read. The values may be stored in a binary file written with <NUM> bit per sample, float values, little-endian ordering. The read values that are needed for the processing are stated in the table below:.

The binaural room impulse responses <NUM> are read from two dedicated files that store individually the left and right ear BRIRs. The time domain samples of the BRIRs are stored in integer wave-files with a resolution of <NUM> bit per sample and <NUM> channels. The ordering of BRIRs in the file is as stated in the following table:.

If there is no BRIR measured at one of the loudspeaker positions, the corresponding channel in the wave file contains zero-values. The LFE channels are not used for the binaural processing.

As a preprocessing step, the given set of binaural room impulse responses (BRIRs) is transformed from time domain filters to complex-valued QMF domain filters. The implementation of the given time domain filters in the complex-valued QMF domain is carried out according to ISO/IEC FDIS <NUM>-<NUM>:<NUM>, Annex B. The prototype filter coefficients for the filter conversion are used according to ISO/IEC FDIS <NUM>-<NUM>:<NUM>, Annex B, Table B. The time domain representation <MAT> with <NUM> ≤ v ≤ Ltrans is processed to gain a complex valued QMF domain filter <MAT> with <MAT>.

The audio processing block of the binaural renderer module <NUM> obtains time domain audio samples <NUM> for Nin input channels from the core decoder and generates a binaural output signal <NUM> consisting of Nout = <NUM> channels.

As the first processing step, the binaural renderer module transforms L = <NUM> time domain samples of the Nin -channel time domain input signal (coming from the core decoder) <MAT> to an Nin -channel QMF domain signal representation <NUM> of dimension Ln = <NUM> QMF time slots (slot index n) and K = <NUM> frequency bands (band index k).

A QMF analysis as outlined in ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. <NUM> with the modifications stated in ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. is performed on a frame of the time domain signal <MAT> to gain a frame of the QMF domain signal <MAT>.

Next, a bandwise fast convolution <NUM> is carried out to process the QMF domain audio signal <NUM> and the QMF domain BRIRs <NUM>. A FFT analysis may be carried out for each QMF frequency band k for each channel of the input signal <NUM> and each BRIR <NUM>.

Due to the complex values in the QMF domain one FFT analysis is carried out on the real part of the QMF domain signal representation and one FFT analysis on the imaginary parts of the QMF domain signal representation. The results are then combined to form the final bandwise complex-valued pseudo-FFT domain signal <MAT> and the bandwise complex-valued BRIRs <MAT> for the left ear <MAT> for the right ear.

The length of the FFT transform is determined according to the length of the complex valued QMF domain BRIR filters Ltrans,n and the frame length in QMF domain time slots Ln such that <MAT>.

The complex-valued pseudo-FFT domain signals are then multiplied with the complex-valued pseudo-FFT domain BRIR filters to form the fast convolution results. A vector mconv is used to signal which channel of the input signal corresponds to which BRIR pair in the BRIR data set.

This multiplication is done bandwise for all QMF frequency bands k with <NUM> ≤ k ≤ Kmax. The maximum band Kmax is determined by the QMF band representing a frequency of either <NUM> or the maximal signal frequency that is present in the audio signal from the core decoder <MAT>.

The multiplication results from each audio input channel with each BRIR pair are summed up in each QMF frequency band k with <NUM> ≤ k ≤ Kmax resulting in an intermediate <NUM>-channel Kmax -band pseudo-FFT domain signal. <MAT> are the pseudo-FFT convolution result <MAT> in the QMF domain frequency band k.

Next, a bandwise FFT synthesis is carried out to transform the convolution result back to the QMF domain resulting in an intermediate <NUM>-channel Kmax -band QMF domain signal with LFFT. time slots <MAT> with <NUM> ≤ n ≤ LFFT and <NUM> ≤ k ≤ Kmax.

For each QMF domain input signal frame with L=<NUM> timeslots a convolution result signal frame with L=<NUM> timeslots is returned. The remaining LFFT - <NUM> timeslots are stored and an overlap-add processing is carried out in the following frame(s).

As a second intermediate signal 826a, 826b a reverberation signal called <MAT> is generated by a frequency domain reverberator module 816a, 816b. The frequency domain reverberator 816a, 816b takes as input.

The frequency domain reverberator 816a, 816b returns a <NUM>-channel QMF domain late reverberation tail.

The maximum used band number of the frequency-dependent parameter set is calculated depending on the maximum frequency.

First, a QMF domain stereo downmix <NUM> of one frame of the input signal <MAT> is carried out to form the input of the reverberator by a weighted summation of the input signal channels. The weighting gains are contained in the downmix matrix MDMX. They are real-valued and non-negative and the downmix matrix is of dimension Nout × Nin. It contains a non-zero value where a channel of the input signal is mapped to one of the two output channels.

The channels that represent loudspeaker positions on the left hemisphere are mapped to the left output channel and the channels that represent loudspeakers located on the right hemisphere are mapped to the right output channel. The signals of these channels are weighted by a coefficient of <NUM>. The channels that represent loudspeakers in the median plane are mapped to both output channels of the binaural signal. The input signals of these channels are weighted by a coefficient <MAT>.

In addition, an energy equalization step is performed in the downmix. It adapts the bandwise energy of one downmix channel to be equal to the sum of the bandwise energy of the input signal channels that are contained in this downmix channel. This energy equalization is conducted by a bandwise multiplication with a real-valued coefficient <MAT>.

The factor ceq,k is limited to an interval of [<NUM>, <NUM>]. The numerical constant ε is introduced to avoid a division by zero. The downmix is also bandlimited to the frequency fmax ; the values in all higher frequency bands are set to zero.

<FIG> schematically represents the processing in the frequency domain reverberator 816a, 816b of the binaural renderer <NUM> in accordance with an embodiment of the present invention.

In the frequency domain reverberator a mono downmix of the stereo input is calculated using an input mixer <NUM>. This is done incoherently applying a <NUM>° phase shift on the second input channel.

This mono signal is then fed to a feedback delay loop <NUM> in each frequency band k, which creates a decaying sequence of impulses. It is followed by parallel FIR decorrelators that distribute the signal energy in a decaying manner into the intervals between the impulses and create incoherence between the output channels. A decaying filter tap density is applied to create the energy decay. The filter tap phase operations are restricted to four options to implement a sparse and multiplier-free decorrelator.

After the calculation of the reverberation an inter-channel coherence (ICC) correction <NUM> is included in the reverberator module for every QMF frequency band. In the ICC correction step frequency-dependent direct gains gdirect and crossmix gains gcross are used to adapt the ICC.

The amount of energy and the reverberation times for the different frequency bands are contained in the input parameter set. The values are given at a number of frequency points which are internally mapped to the K = <NUM> QMF frequency bands.

Two instances of the frequency domain reverberator are used to calculate the final intermediate signal <MAT>. The signal <MAT> is the first output channel of the first instance of the reverberator, and <MAT> is the second output channel of the second instance of the reverberator. They are combined to the final reverberation signal frame that has the dimension of <NUM> channels, <NUM> bands and <NUM> time slots.

The stereo downmix <NUM> is both times scaled 821a,b according to a correlation measure <NUM> of the input signal frame to ensure the right scaling of the reverberator output. The scaling factor is defined as a value in the interval of <MAT> linearly depending on a correlation coefficient ccorr between <NUM> and <NUM> with <MAT> and <MAT> where <MAT> means the standard deviation across one time slot n of channel A , the operator {*} denotes the complex conjugate and <MAT> is the zero-mean version of the QMF domain signal ŷ in the actual signal frame.

ccorr is calculated twice: once for all channels A, B that are active at the actual signal frame F and are included in the left channel of the stereo downmix and once for all channels A, B that are active at the actual signal frame F and that are included in the right channel of the stereo downmix.

NDMX,act is the number of input channels that are downmixed to one downmix channel A (number of matrix element in the Ath row of the downmix matrixMDMX that are unequal to zero) and that are active in the current frame.

The scaling factors are smoothed over audio signal frames by a <NUM>st order low pass filter resulting in smoothed scaling factors c̃scale = [c̃scale,<NUM>,c̃scale,<NUM>].

The scaling factors are initialized in the first audio input data frame by a time-domain correlation analysis with the same means.

The input of the first reverberator instance is scaled with the scaling factor c̃scale,<NUM> and the input of the second reverberator instance is scaled with the scaling factor c̃scale,<NUM>̃.

Next, the convolutional result <NUM>, <MAT>, and the reverberator output 826a, 826b, <MAT>, for one QMF domain audio input frame are combined by a mixing process <NUM> that bandwise adds up the two signals. Note that the upper bands higher than Kmax are zero in <MAT> because the convolution is only conducted in the bands up to Kmax·.

The late reverberation output is delayed by an amount of d = ((Ltrans -<NUM>+<NUM>)/<NUM>+<NUM>)+<NUM> time slots in the mixing process.

The delay d takes into account the transition time from early reflections to late reflections in the BRIRs and an initial delay of the reverberator of <NUM> QMF time slots, as well as an analysis delay of <NUM> QMF time slots for the QMF analysis of the BRIRs to ensure the insertion of the late reverberation at a reasonable time slot. The combined signal <MAT> at one time slot n calculated by <MAT>.

One <NUM>-channel frame of <NUM> time slots of the QMF domain output signal <MAT> is transformed to a <NUM>-channel time domain signal frame with length L by the QMF synthesis according to ISO/IEC <NUM>-<NUM>:<NUM>, subclause <NUM>. yielding the final time domain output signal <NUM>, <MAT>.

A further embodiment of the inventive method is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. The data carrier, the digital storage medium or the recorded medium are typically tangible and/or nontransitionary.

A further embodiment of the invention method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein.

A further embodiment comprises a processing means, for example, a computer or a programmable logic device, configured to, or programmed to, perform one of the methods described herein.

Claim 1:
A method for processing an audio signal (<NUM>, <NUM>) in accordance with a room impulse response (<NUM>, <NUM>), the method comprising:
separately processing (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, 816a, 816b) the audio signal (<NUM>, <NUM>) with an early part (<NUM>, <NUM>) of the room impulse response (<NUM>, <NUM>) and with a late reverberation (<NUM>) of the room impulse response (<NUM>, <NUM>) or a synthetic reverberation, wherein the separate processing comprises:
processing the audio signal (<NUM>, <NUM>) with the early part (<NUM>, <NUM>) of the room impulse response (<NUM>, <NUM>) during a first process,
processing the audio signal (<NUM>, <NUM>) with the late reverberation (<NUM>) of the room impulse response (<NUM>, <NUM>) or with the synthetic reverberation during a second process that is different and separate from the first process, and
changing from the first process to the second process at a transition from the early part to the late reverberation in the room impulse response; and
combining (<NUM>, <NUM>, <NUM>) the audio signal processed with the early part (<NUM>, <NUM>, <NUM>) of the room impulse response (<NUM>, <NUM>) and the audio signal (<NUM>, <NUM>, 826a, 826b) processed with the late reverberation (<NUM>) of the room impulse response (<NUM>, <NUM>) or with the synthetic reverberation,
wherein the transition from the early part (<NUM>, <NUM>) to the late reverberation (<NUM>) in the room impulse response (<NUM>, <NUM>) is determined as a time when a correlation measure reaches a threshold,
wherein the correlation measure describes with regard to the room impulse response a similarity of a decay in acoustic energy comprising an initial state and of the decay in acoustic energy starting at a point in time, said point in time following the initial state over a predefined frequency range,
wherein the threshold is set dependent on the correlation measure at a time of the first reflection (<NUM>, <NUM>) in the early part (<NUM>, <NUM>) of the room impulse response (<NUM>, <NUM>).