March 2007
Real-time binaural sound generation Using TI C6713 DSK board
REAL-TIME BINAURAL SOUND GENERATION USING TI C6713 DSK
BOARD
A Thesis
Submitted
To
Electrical Engineering Department
University of Bridgeport, CT, USA
Submitted
By
Vaibhav Bhatnagar
Student ID : 0695161
[email protected]
Academic Advisor
Prof. Navarun Gupta
Master Thesis
Vaibhav Bhatnagar 0695161
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March 2007
Real-time binaural sound generation Using TI C6713 DSK board
Table of contents
Title
Page
1. Abstract
3
2. Introduction
3
a. Introduction to DSK board
3
3. Methodology
4
4. Results
8
5. Conclusion
8
6. References
8
7. Authors biography
8
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Real-time binaural sound generation Using TI C6713 DSK board
ABSTRACT
Traditionally 3D sound generation involves the use of multiple speakers that are
strategically placed, and have appropriate lags in the sounds emanating from them. Using Head
Related Transfer Functions (HRTFs), a realistic binaural sounds can be generated using a pair
of headphones.
This work describes that how a single channel audio can be transformed into binaural (left /
right channels) using HRTFs. The implementation has been performed on a C6713 DSK Texas
Instrumentation (TI) kit.
Current sound specialization systems use HRTFs, represented by the corresponding impulse
response sequences, the Head-Related Impulse Responses (HRIRs). By convolution, a singlechannel digital audio signal can be converted in two components (left and right). Whenever, the
two channels are delivered to the listener through headphones, the sound seems to emanate from
the source location corresponding to the HRIR pair used for the specialization process.
Digital signal processors have become ubiquitous because of their versatility, and low cost. TI
C713 is ideally suited for binaural sound synthesis from HRTFs because its high-performance,
advanced very-long-instruction-word (VLIW) architecture makes this DSP an excellent choice
for multi-channel and multifunction applications. This work associates a real-time
demonstration.
INTRODUCTION
In recent years, an interest of binaural sound has increased significantly. There is much work has
been found in literature for capturing HRTF coefficients around a humane body that are useful
to realize it in practice. The DSP lab of Florida International University facilitates a database
contains HRTF and relevant anthropometric data of 15 subjects. The data may be useful in
studying or implementing 3D sound specialization / localization and their relation to the
geometric features of the head and outer ear of the subjects.
A binaural sound is the sound or speech that give a 3-D effect to the ears of a listener. Moreover,
a sound generation A user can feel the movements in any directions around his head.
During this work, we use a single channel HRTF coefficients from DSP lab FIU, which are
useful for implementation of an stereo FIR filter on DSK board in order to generate real-time
binaural sound. Before going in to detail, an introduction to the hardware is necessary.
INTRODUCTION TO DSK C6713 TI BOARD
Digital Signal Processors such as the TMS320(C6x) family of processors that are similar to fast
special-purpose microprocessors with a special type of architecture and an instruction set
appropriate for a signal processing in real time [1]. The TMS320DSK6713 DSK starter kit plays
a great role here. This starter kit is a critical invention of Texas Instruments. The essential
properties of DSK6713 starter kit that make it useful for real-time are:
 DSK board is powerful and inexpensive ($395.
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Real-time binaural sound generation Using TI C6713 DSK board
 C6713 is a floating-point digital signal processor
 Onboard codec TLV320AIC23 (AIC23) serves for analog to digital converter (ADC)
and digital to analog converter (DAC) conversion.
 12-MHz system clock.
 Supports a sampling rate from 8 to 96 KHz.
 Two 80-pin connectors provide an external peripheral and external memory interface
(IMIF) with light-emitting diodes (LEDs) and liquid-crystal displays (LCDs) for spectrum
display.
 16 MB (megabytes) of synchronous dynamic random access memory (SDRAM) and
256kB (kilobytes) of flash memory.
 Input/outputs : MIC IN for microphone input, LINE IN for line input, LINE OUT for line
output, and HEADPHONE for a headphone output (multiplexed with line output).
 Four users dip switches on the DSK board for a feedback control interface.
 Code composer studio (CCS) is a software interface that can include Matlab also.
The DSK hardware is used for stereo FIR implementation, whereas the FIR has designed
with the one channel HRTFs in Matlab.
Rest of the paper is organized as: METHODOLOGY describes method used to obtain the
results, in RESULTS the hardware outcome has been discussed, CONCLUSION concludes
the end of the paper, and REFERENCES give some important papers, taken in to account.
METHODOLOGY
Brown and Duda in [3] proposed an “structural” model for binaural sound synthesis. A
customizable functional model developed by Algazi models a listener’s head with only 3 simple
anatomical measurements [4]. Like Brown and Duda there are many models available to
generate binaural sound and measure HRTF. As mentioned earlier, we use HRTF coefficients
provided openly by DSP lab, FIU. In addition, a simple FIR filter can be designed in C language
and can lead a further implementation as a Real Time FIR Stereo Filter on a powerful DSK
board.
Filtering is one of the most useful signal processing operation. Moreover, TMS320C6x
instruction set [1] and architecture makes DSK well suited for such filtering operations. An
analog filter operates on continuous signals and is typically realized with discrete components
such as operational amplifiers, resistors, and capacitors. However, a digital filter, such as an FIR
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Real-time binaural sound generation Using TI C6713 DSK board
filter, operates on discrete-time signals and can be implemented with a DSP chip such as the
TMS320C6x. This involves use of an ADC to capture an external input signal, process the input
samples, and send the output through a DAC. A number of tools are available to design an FIR
filter that can be further implemented on hardware. The filter design consists of an
approximation of a transfer function with a resulting set of coefficients. Here we use the HRTF
coefficients that have taken from FIU (Florida Institute of Technology) available for all
directions on a humane head [1].
The convolution of FIR filters can be approximated with a finite number of terms by equation 1.
N 1
y (n) =
 h( k ) x ( n  k )
(1)
k 0
If the input is a unit impulse x (n) = δ (0), the output impulse response will be y (n) = h (k). If the
filter has N coefficients h (0), h (1) …h (N-1), and N input samples x (n), x (n-1)… x (n-(N-1)).
Equation (1) shows that an FIR filter can be implemented with knowledge of the input x (n) at
time n and of the delayed inputs x (n-k). It is a non-recursive, no feedback, and non-causal filter.
Filters with feedback are transversal and tapped-delay filters. Moreover, the Z-transform of
equation (1) with zero initial conditions yields
Y (z) = h(0)X(z)+h(1)z-1 X(z)+h(2)z-2 X(z)+ …+h(N-1)z-(N-1)X(z)
(2)
Equation (1) represents a convolution in time domain between the coefficients and the input
samples, whereas equation 2 is equivalent to a multiplication in the frequency domain.
Y (z) = H (z) X (z),
(3)
where H (z) = ZT [h (k)] is the transfer function, which indicates N -1 poles located at the origin.
Hence this FIR filter is inherently stable, with its poles located inside the unit circle. We usually
describe an FIR filter as a filter with “no poles”. A very useful feature of an FIR filter is that it
can guarantee a linear phase. In speech analysis linear phase feature can avoid the critical phase
distortion because due to linear phase, all input sinusoidal components are delayed by the same
amount. Otherwise, harmonic distortion can occur. Linear Phase filters are FIR filters; but, not
all FIR filters have linear phase.
By using FIR filter we can implement a real time stereo filter. In this project, 24 HRIR as
coefficients are used for FIR filter implementation; 12 sound directions and 24 HRIR for both
right and left ear. Size of each coefficient file is 256. To generate binaural sound we are using
12 directions.
To understand the all directions we need to understand an spherical co-ordinate system that has
two parts (Fig. 1):
1) Azimuth
2) Elevation
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Real-time binaural sound generation Using TI C6713 DSK board
Figure 1.
For example, we can consider and HRIR having azimuth +300 and elevation 540. Figure 2 shows
the HRIR in time domain and Figure 3 shows the HRTF in frequency domain for the same.
Here with the following C program we can understand what exactly FIR filter doing.
HRIR of subject: XL
Az = +30, El = +54
0.5
Left
Right
0.4
0.3
magnitude
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
0
0.5
1
1.5
Figure
time (sec) 2.
2
2.5
3
-3
x 10
Figure 2.
//Fir.c FIR filter. Include coefficient file with length N
#include "bs2700.cof"
//coefficient file
#include "dsk6713_aic23.h"
//codec-dsk support file
Uint32 fs=DSK6713_AIC23_FREQ_8KHZ;
//set sampling rate
int yn = 0;
//initialize filter's output
short dly[N];
//delay samples
interrupt void c_int11()
{
short i;
Master Thesis
//ISR
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Real-time binaural sound generation Using TI C6713 DSK board
HRTFs of subject: XL
Az = +30, El = +54
1
10
Left
Right
0
magnitude
10
-1
10
-2
10
2
10
3
4
10
10
5
10
frequency (Hz)
Figure 3.
dly[0]=input_sample(); //input newest sample
yn = 0;
//initialize filter's output
for (i = 0; i< N; i++)
yn += (h[i] * dly[i]); //y(n) += h(i)* x(n-i)
for (i = N-1; i > 0; i--) //starting @ end of buffer
dly[i] = dly[i-1];
//update delays with data move
output_sample(yn >> 15); //scale output filter sample
return;
}
void main()
{
comm_intr();
while(1);
}
//init DSK, codec, McBSP
//infinite loop
A buffer dly [N] is created for the delay samples. The newest input sample, x (n), is acquired
through dly [0] and stored at the beginning of the buffer. The coefficients are stored in another
buffer, h [N], with h [0] at the beginning of the coefficients’ buffer. The samples and coefficients
are then arranged in their respective buffer.
Two for loops are used within the interrupt service routing (we will also implement an FIR filter
using one loop). The first loop implements the convolution equation with N coefficients and N
delay samples for a specific time n. At time n the output is
y(n) = h(0)x(n) + h(1)x(n-1) + … + h(N-1)x(n-(N-1))
(4)
The delay samples are then updated within the second loop to be used for calculating y (n) at
time n+1, or y (n+1). The newly acquired input sample always resides at the beginning of the
samples buffer (in this example). The memory location that contained the sample x (n) now
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Real-time binaural sound generation Using TI C6713 DSK board
contains the newly acquired sample x (n + 1). The output y (n + 1) at time n+1 is then calculated.
This scheme uses a data move to update the delayed samples.
In the final program we use 2 dimensional filter coefficients files. The looping is same as above
but result generates the binaural sound with the help of 24 HRIR files of 12 directions.
RESULTS
There are no physical results to show. Anybody can feel the generated sound by using the single
pair of headphones. Normally, the sound moves around the head. This effect shows that sound is
binaural. In practical life to generate the binaural sound we need to place lot of sound sources
around the listener so that he can feel the mono sound in a binaural fashion nonetheless with the
help of HRIR files we could perform it in a real-time. According to our personnel experience
with the result, this is effective way of producing 3-D sound. And the best effect we realize in the
azimuth +900 to -900 mainly back of head.
CONCLUSION
With the help of available HRTF coefficients, an stereo FIR filter has been designed,
implemented, and validated on a DSK C6713 TI board. However, the sound quality is not clear
but a person can still realize a sound motion. A clear sound can be achieved by replacing HRTF
coefficients with HRIR coefficients. Moreover, we need to optimize the program for higher
sampling rate and more directions that should be included to attain a perfect 3-D sound.
REFERENCES
[1] Digital Signal Processing and Applications with the C6713 and C6416 DSK, Rulph
Chassaing, Wiley Interscience (2005). ISBN 0-471-69007-4.
[2] “Decomposition of Head Related Impulse Responses by Selection of Conjugate Pole Pairs,
Kenneth John Faller II1, Armando Barreto1, Navarun Gupta2 and Naphatali Rishe3.
[3] C. P. Brown and R. O. Duda, “A structural model for binaural sound sysnthesis, “Ieee
Transactions on speech and Audio Processing, vol. 6, pp. 476-448, 1998.
[4] V.R. Algazi, C. Avendano, and R.O. Duda, “Estimation of a spherical-head model from
anthropometry,” Journal of the Audio Engineering Society, vol. 49, pp. 472-479, 2001.
AUTHOR(S) BIOGRAPHY
Vaibhav Bhatnagar is Graduate Assistant in Electrical Engineering at the University of
Bridgeport, Bridgeport, CT. He did his undergraduate in Electronics and Communications at the
Uttar Pradesh Technical University, Lucknow in 2004. He is pursuing his Masters of Science,
Electrical Engineering at the University of Bridgeport, CT. He graduates in May 2007.
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