2014-02-23 21:11:01 -08:00
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#ifndef ALC_HRTF_H
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#define ALC_HRTF_H
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2019-02-07 08:38:49 -08:00
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#include <array>
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2019-07-28 11:28:36 -07:00
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#include <cstddef>
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2019-01-08 23:44:08 -08:00
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#include <memory>
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2018-12-25 11:09:41 -08:00
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#include <string>
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2014-02-23 21:11:01 -08:00
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#include "AL/al.h"
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2018-11-22 07:54:29 -08:00
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#include "almalloc.h"
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2019-09-25 02:11:37 -07:00
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#include "alspan.h"
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2019-07-28 11:28:36 -07:00
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#include "ambidefs.h"
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#include "atomic.h"
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#include "vector.h"
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2019-07-28 21:29:59 -07:00
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2018-01-11 03:53:25 -08:00
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#define HRTF_HISTORY_BITS (6)
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#define HRTF_HISTORY_LENGTH (1<<HRTF_HISTORY_BITS)
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#define HRTF_HISTORY_MASK (HRTF_HISTORY_LENGTH-1)
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2019-12-11 02:24:44 -08:00
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#define HRIR_BITS (7)
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#define HRIR_LENGTH (1<<HRIR_BITS)
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#define HRIR_MASK (HRIR_LENGTH-1)
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#define MIN_IR_LENGTH (8)
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2018-01-11 03:53:25 -08:00
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2019-11-28 09:46:16 -08:00
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using float2 = std::array<float,2>;
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using HrirArray = std::array<float2,HRIR_LENGTH>;
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2018-01-11 03:53:25 -08:00
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2019-11-28 06:10:36 -08:00
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struct HrtfStore {
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2019-09-14 18:27:57 -07:00
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RefCount mRef;
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2017-04-06 13:00:29 -07:00
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2016-07-07 10:26:42 -07:00
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ALuint sampleRate;
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2019-09-13 09:38:35 -07:00
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ALuint irSize;
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2017-10-23 13:26:35 -07:00
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2019-01-28 20:31:58 -08:00
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struct Field {
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2019-02-27 23:13:40 -08:00
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ALfloat distance;
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2019-05-22 10:58:18 -07:00
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ALubyte evCount;
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2019-01-28 20:31:58 -08:00
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};
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2019-02-27 23:13:40 -08:00
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/* NOTE: Fields are stored *backwards*. field[0] is the farthest field, and
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* field[fdCount-1] is the nearest.
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*/
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2019-09-13 09:38:35 -07:00
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ALuint fdCount;
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2019-05-22 10:58:18 -07:00
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const Field *field;
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2016-07-07 10:26:42 -07:00
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2019-05-22 10:58:18 -07:00
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struct Elevation {
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ALushort azCount;
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ALushort irOffset;
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};
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Elevation *elev;
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2019-11-28 09:46:16 -08:00
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const HrirArray *coeffs;
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2017-04-07 08:46:50 -07:00
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const ALubyte (*delays)[2];
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2019-01-24 10:05:37 -08:00
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void IncRef();
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void DecRef();
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DEF_PLACE_NEWDEL()
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2016-07-07 10:26:42 -07:00
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};
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2014-02-23 21:11:01 -08:00
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2017-01-18 19:16:24 -08:00
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2018-11-22 06:59:32 -08:00
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struct HrtfState {
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2019-11-29 08:33:46 -08:00
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alignas(16) std::array<float,HRTF_HISTORY_LENGTH> History;
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2018-11-22 06:59:32 -08:00
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};
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2018-01-11 03:53:25 -08:00
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2019-06-18 06:20:35 -07:00
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struct HrtfFilter {
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2019-07-31 10:46:33 -07:00
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alignas(16) HrirArray Coeffs;
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2019-11-29 08:33:46 -08:00
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ALuint Delay[2];
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float Gain;
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2018-11-22 06:59:32 -08:00
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};
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2018-01-11 03:53:25 -08:00
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2018-11-22 06:59:32 -08:00
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struct DirectHrtfState {
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2018-01-11 03:53:25 -08:00
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/* HRTF filter state for dry buffer content */
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2019-09-13 09:38:35 -07:00
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ALuint IrSize{0};
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2019-09-03 23:19:24 -07:00
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al::FlexArray<HrirArray,16> Coeffs;
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2018-11-22 07:54:29 -08:00
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2019-09-03 23:19:24 -07:00
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DirectHrtfState(size_t numchans) : Coeffs{numchans} { }
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2019-01-12 01:25:33 -08:00
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static std::unique_ptr<DirectHrtfState> Create(size_t num_chans);
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2018-11-22 14:36:37 -08:00
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2019-09-11 03:59:53 -07:00
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DEF_FAM_NEWDEL(DirectHrtfState, Coeffs)
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2018-11-22 06:59:32 -08:00
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};
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2018-01-11 03:53:25 -08:00
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2019-12-06 23:11:26 -08:00
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struct EvRadians { float value; };
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struct AzRadians { float value; };
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2018-02-17 22:12:54 -08:00
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struct AngularPoint {
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2019-12-06 23:11:26 -08:00
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EvRadians Elev;
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AzRadians Azim;
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2018-02-17 22:12:54 -08:00
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};
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2018-01-11 03:53:25 -08:00
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2019-11-28 08:24:29 -08:00
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al::vector<std::string> EnumerateHrtf(const char *devname);
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2019-11-28 14:51:45 -08:00
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HrtfStore *GetLoadedHrtf(const std::string &name, const char *devname, const ALuint devrate);
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2015-10-06 00:23:11 -07:00
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2019-11-29 08:33:46 -08:00
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void GetHrtfCoeffs(const HrtfStore *Hrtf, float elevation, float azimuth, float distance,
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float spread, HrirArray &coeffs, ALuint (&delays)[2]);
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2014-02-23 21:11:01 -08:00
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2017-01-18 19:16:24 -08:00
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/**
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* Produces HRTF filter coefficients for decoding B-Format, given a set of
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2018-05-15 22:11:10 -07:00
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* virtual speaker positions, a matching decoding matrix, and per-order high-
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* frequency gains for the decoder. The calculated impulse responses are
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2019-09-24 22:27:12 -07:00
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* ordered and scaled according to the matrix input.
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Decode directly from B-Format to HRTF instead of a cube
Last time this attempted to average the HRIRs according to their contribution
to a given B-Format channel as if they were loudspeakers, as well as averaging
the HRIR delays. The latter part resulted in the loss of the ITD (inter-aural
time delay), a key component of HRTF.
This time, the HRIRs are averaged similar to above, except instead of averaging
the delays, they're applied to the resulting coefficients (for example, a delay
of 8 would apply the HRIR starting at the 8th sample of the target HRIR). This
does roughly double the IR length, as the largest delay is about 35 samples
while the filter is normally 32 samples. However, this is still smaller the
original data set IR (which was 256 samples), it also only needs to be applied
to 4 channels for first-order ambisonics, rather than the 8-channel cube. So
it's doing twice as much work per sample, but only working on half the number
of samples.
Additionally, since the resulting HRIRs no longer rely on an extra delay line,
a more efficient HRTF mixing function can be made that doesn't use one. Such a
function can also avoid the per-sample stepping parameters the original uses.
2016-08-11 23:20:35 -07:00
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*/
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2019-11-28 06:10:36 -08:00
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void BuildBFormatHrtf(const HrtfStore *Hrtf, DirectHrtfState *state,
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2019-09-25 02:11:37 -07:00
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const al::span<const AngularPoint> AmbiPoints, const ALfloat (*AmbiMatrix)[MAX_AMBI_CHANNELS],
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const ALfloat *AmbiOrderHFGain);
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Decode directly from B-Format to HRTF instead of a cube
Last time this attempted to average the HRIRs according to their contribution
to a given B-Format channel as if they were loudspeakers, as well as averaging
the HRIR delays. The latter part resulted in the loss of the ITD (inter-aural
time delay), a key component of HRTF.
This time, the HRIRs are averaged similar to above, except instead of averaging
the delays, they're applied to the resulting coefficients (for example, a delay
of 8 would apply the HRIR starting at the 8th sample of the target HRIR). This
does roughly double the IR length, as the largest delay is about 35 samples
while the filter is normally 32 samples. However, this is still smaller the
original data set IR (which was 256 samples), it also only needs to be applied
to 4 channels for first-order ambisonics, rather than the 8-channel cube. So
it's doing twice as much work per sample, but only working on half the number
of samples.
Additionally, since the resulting HRIRs no longer rely on an extra delay line,
a more efficient HRTF mixing function can be made that doesn't use one. Such a
function can also avoid the per-sample stepping parameters the original uses.
2016-08-11 23:20:35 -07:00
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2014-02-23 21:11:01 -08:00
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#endif /* ALC_HRTF_H */
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