A Comparative Study of Combination
with Different LSB Techniques in MP3
Steganography
Mohammed Salem Atoum
Faculty of Computing, Universiti Teknologi Malaysia
Moh_atoom1979@yahoo.com
Abstract
Steganography hides the existence of the data inside any cover file. There are different file
formats used in steganography like text, image, audio and video. Out of these file formats
audio steganography is followed in this paper .One of the major objective of hiding data
using audio steganography is to hide the data in an audio file, so that the changes in the
intensity of the bits of host must not be detect by human auditory system. The focus of
this paper is on time domain technique i.e. LSB technique of audio steganography.
Method used in the paper hides the data in combination of LSBs instead of hiding the
data in least significant bit. Results are compared by using parameters PSNR, BER and
correlation.
Introduction
The increasing Internet usage stems from the growing availability of the global communication
technology that has led to electronically induced information gathering and distribution. However, the
challenge it presents in terms of information security is enormous. Every Internet user interest lies in
having a secure transaction, communication and information across the transmission link, but in reality,
much communication are infiltrated, jabbed and altered. Information confidentiality was enacted by the
CIA as one of the key principles of a secure communication and if abused attracts penalty. However, many
communications still fall short of achieving a secured information transmission across the global network
(the Internet). The need to secure information within the global network is of paramount importance so
that user information is preserved until it reaches its destination undisclosed.
A lot of sensitive information goes through the Internet on frequent basis. This information could be
military codes, government dealings, and personal data, the route, sender/ receiver, the content of such
information requires that they are protected against hacking and infiltration. Therefore, providing a
secure framework that conceals information content and sender/receiver identity should be an urgent
matter of interest. There are two known approaches to information confidentiality; they are cryptography
and steganography [1]. Cryptography has long existed as the method for securing data; it works with set
of rules that transforms information into unrecognizable format. The rules are used to serve for
authentication purposes, because only the one who knows the rules can decipher the encrypted
information [2]. The advent of steganography provides more security features since the information is
disguised in the sense that the information does not give away its content and identity of sender and
receiver within the communication link. Cryptography and steganography techniques both make use of
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data encryption approach but Cryptography encrypts plainly its secret message thereby making the
content and the user’s details vulnerable to exploitation. Steganography technique protects both
information content and identity of a person’s transmitting the information, whereas only information is
concealed with cryptography [3].
Steganography operates by embedding a secret message which might be a copyright mark, or a covert
communication, or a serial number in a cover such as a video film, an audio recording, or computer code
in such a way that it cannot be accessed by unauthorised person during data exchange. A cover containing
a secret data is known as a Stego-object [3]. After data exchange; it is advisable for both parties (sender
and receiver) to destroy the cover in order to avoid accidental reuse. The basic model of a steganography
system is shown in the Figure1 [4]. The model contains two inputs and two processes, the inputs are a
cover medium and secret message both can be any image, audio, video and so on. Two processes contain
embedding and extracting processes.
Sender sides
Cover
Embedding Process
Stego object
Message
Key
Receiver sides
Stego object
Extracting Process
Message
Key
Figure 1: Basic Model of Steganography
The embedding process is used to hide secret messages inside a cover; the embedding process is
protected by a key if using secret key steganography and public key Steganography types, or without a key
if using pure Steganography type. When using key, only those who possess the secret key can access the
hidden secret message, while the extracting process is applied to a possibly modified carrier and returns
the hidden secret message. Until recently, steganography utilized image files for embedding information
across the Internet network. However recently, its use has been extended to audio steganography. The
usage of audio signal as an embedding platform for information hiding is due to the fact that it has
sophisticated features that allow information hiding, though difficult its robustness counts. In audio
steganography, various signal processing techniques can be utilized to hide information in an audio file in
such a way that it cannot be visually interpreted [5]. This approach has brought about the growing
research interest in the use of digital audio signal for embedding information. The sensitiveness of audio
files to delay presents more challenges to the design objective of steganography. There are three
fundamental properties to the design of steganography. They are: 1) imperceptibility, 2) robustness and
3) capacity. However, there are other properties such as computational time that must be considered
when dealing with different types of applications (information) such as broadcast monitoring applications
in a global network. In most cases it requires real time processing and thereby cannot tolerate any form of
delay [6].
The rest of this paper is organized as follows: A detailed introduction of audio steganography and MP3
file structure, the existing methods for MP3 steganography, then experimental results and conclusion.
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AUDIO STEGANOGRAPHY
The techniques of Steganography were originally developed and used for images. Researchers in the
field then started studying on how the techniques can be used on audio media. Hence, the introduction
and development of the known algorithms for audio steganography was founded. As the known
steganography techniques are mostly used for images there are not many methods for audio steganalysis.
Thus, audio Steganography provides considerably better security [5].
In audio Steganography, many types of file can be used as a cover of steganography such as Waveform
Audio File Format (WAVE, or more commonly known as WAV due to its filename extension) or MPEG1 or MPEG-2 Audio Layer III (MP3). Similarly, secret messages that are embedded can be of secured types
such as text or speech. MP3 is the most popular compression format for digital audio. In steganography,
which uses MP3 as a cover, secret message can be embedded during compression and after compression
[12-13].
This section explains and discusses MP3 file structure, MP3 encoding and MP3 frames header
MP3 file structure
The content of MP3 files depends on the type of encoding used. The common structures of MP3 files
consist of three components, they are Tag, Padding bytes and Frames, and these are shown in Figure 2.
Figure 2: MP3 File Structure
Tags are of two types, the ID3v1 and the ID3v2, and the later usually utilize the end section of the file to
post-pended information. The length of ID3v1 is 128 bytes separated to seven fields which composed of
the artist name, album, song title and genre. Its drawbacks are that it has a static size and also lack
flexibility of implementation. Also, not all MP3 files accept the ID3v1 tagging system. However, its second
ID3v2 presents a more adaptive standard since it is flexible and has a tagging system that pre-pended
information before it is sent [7]. The ID3v2 tags consist of its own frames which are capable of storing
various bits of data, for instance, the standard of character strings such as the artist name, song title or
more advanced information concerning the way the file was programmed are all the data that is
embedded in the signal. The advantages of the ID3v2 tags are that useful hints to the decoder are
provided prior to transmission and that there is no size limit to information capacity provided in its prepending system [8]. The Padding byte provides additional data embedding; the data provided are added
to the frame. Its working principle is that on the event of the encoding, additional data are evenly filled to
the frame; this byte can be found in Constant Bit Rate (CBR) so as to ensure that frames are of the same
size [9].
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MP3 Encoding
MP3 encoding refers to quality enhancer of both compressed sound and the size of compressed sound
file or compression ratio. The three encoding bit rates used by different encoders include the CBR,
Variable Bit Rate (VBR) and Average Bit Rate (ABR).
CBR refers to a standard encoding mechanism used by basic encoders. In this encoding mechanism,
each frame used the same bit rate in the audio data. The bit rate is fixed in the whole of MP3 file, as the
same number of bits is used for each part of the MP3 file. However, the quality of MP3 is variable. These
techniques can be used to predict the size of encoded file and can be calculated by multiplying the bit rate
chosen to encode with the length of a song [10].
VBR is a technique that can keep the quality of audio files during the encoding process. In this
technology the quality of the sound can be specified but the size of the sound file remains unpredictable
[10].
ABR is a mode that uses higher bit rate for the part of music by choosing the encoder adds bits. The
final result showed that the quality is higher than CBR. Moreover, the average file size remains
predictable [10].
RELATED WORKS
Little research's using MP3 as a cover in steganography [14]. Most researchers work in wave
steganography. The following methods explain and discuss the current MP3 steganography methods:
1. M4M method: Bhattacharyya and et al [15] proposed a new method for imperceptible audio data
hiding for an audio file of wav or mp3 format. This approach based on the Mod 16 Method (M16M) [16]
designed for image named Mod 4 Method (M4M) along with a Number Sequence Generator Algorithm to
avoid embedding data in the consecutive indexes of the audio, which will eventually help in avoiding
distortion in the audio quality. The input messages can be in any digital form, and are often treated as a
bit stream. Embedding positions are selected based on some mathematical function which de-ends on the
data value of the digital audio stream. Data embedding is performed by mapping each two bit of the secret
message in each of the seed position, based on the remainder of the intensity value when divided by 4.
Extraction process starts by selecting those seed positions required during embed-ding. At the receiver
side other different reverse operation has been carried out to get back the original information.
2. M16M method: Bhattacharyya and et al [17] proposed a new method for imperceptible audio data
hiding for an audio file of wav or mp3 format. This approach based on the Mod 16 Method (M16M) [16]
designed for image named Mod 16 Method for audio (M16MA) along with a Number Sequence Generator
Algorithm to avoid embedding data in the consecutive indexes of the audio, which will eventually help in
avoiding distortion in the audio quality. The input messages can be in any digital form, and are often
treated as a bit stream. Embedding positions are selected based on some mathematical function which deends on the data value of the digital audio stream. Data embedding is performed by mapping each four bit
of the secret message in each of the seed position, based on the remainder of the intensity value when
divided by 16. Extraction process starts by selecting those seed positions required during embedding. At
the receiver side other different reverse operation has been carried out to get back the original
information.
3. Unused Header Bit Stuffing (UHBS): The MP3 frame headers are made up of fields such as
the private bit, original bit, copyright bit, and emphasis bit but its usage are mostly omitted in some MP3
players. These fields are the important aspect of the frame that aids the interpretation of information
concealed within the audio signal. They can be properly used to embed undisclosed massage by replacing
the bit stream of undisclosed massage through the bits in the field. However, if in the process of replacing
the bit stream with the bit in the field fails, the actual content of the secret message received within the
frame will be lost and that will make the signal recovery more challenging [9]. The work by [18]
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highlighted on the possibility that audio steganography can achieve good capacity and robustness
through the use of 4 bits in each header frame of the audio signal to embed secret messages.
4. Padding Byte Stuffing (PBS): Padding byte stuffing was recently established as one of the
techniques for steganography. Its approach is relatively straightforward in terms of implementation. It
represents fine regular storage capability and has the ability to program 1 byte of information for each
frame as long as padding bytes are accessible. The MP3 file is a given example of the material medium
that can well utilize the padding byte stuffing method because it can allow for hundreds of frames in one
secret message, especially when the filling bytes cannot take any more audio information [18].
5. Embedding in Before All Frames (BAF): BAF was developed by [19]. Their approach embeds
text file to MP3 file. The text file is encrypted by using RSA algorithm to increase the security of
undisclosed secret message. The first frame will be filled with encrypted information. This process is
repeated sequentially until the frame headers are filled. The capacity of about 15 KB is utilized when
encryption algorithm is used otherwise it takes about 30 KB for the MP3 file. Even though there are
chances of the secret message being sniffed, for this approach, its advantages are enormous, for instance,
the method of padding and the unused bit even after the frames must have been filled, provides more
encoding capability.
6. Embedding in Between Frames (BF): [20] Developed steganography technique that
embedded between frames (BF). It also embeds text file to MP3 file like the BAF and encrypts information
in bits format by using RSA algorithm in order to increase the protection of concealed secret messages.
The BF differs from the BAF in the way the text files are inserted into the frames. It does not start with the
first frame it sees but selects the frame of its choice. On the other hand, the capacity of the BF in
comparison to the BAF utilizes the capacity of about 40 MB with encryption algorithm but requires 80
MB on original format. BF likewise provides good capacity for embedding text file in more capacity but it
is still prone to attack. We draw inferences based on the literatures accessed that the method of
embedding information after compression is a challenging task since the embedding process is done after
compression and the text file are located in the unused bit location and not in the audio data. This
technique provides a platform that is prone to attack because the content of the secret message sent can
be easily deciphered by a third party sniffing through the communication link. It also provides only
limited capacity for secret message hiding. However, if the LSB technique is used to insert speech in MP3
file with the use of 2, 3 and 4 bit exchange in audio data (8-bit for sample), the problem of capacity can be
resolve. In addressing the problem of security, the use of key as the lock for concealed secret message is a
foreseeable approach that can achieve maximum security for concealed secret messages.
7. New Secure Scheme in Audio Steganography (SSAS): Atoum et al [21] proposed model
uses Mathematical equation to partition secret message into blocks, and applies permutation equation to
re-order the blocks position, which will change and create new secret message addressing. So, if attackers
detect the Stego object they can’t know the secret message contains. In addition, the proposed model
applied a mathematical model for embedding, and also used map for extracting secret message. All these
techniques increase the security of Stego object and also reduce the probability to attack the secret
message or exchange it.
Literature review shows that the method of embedding information after compression. There are
several methods for embedding secret message after compression namely: M4M, M16M, UHBS, PBS, BF,
BAF and SSAS. The strengths and weaknesses are shown in Table1.
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Table 1 shows the strength and weakness for MP3 methods
Techniques
Author and Year
et al.,
Strength
M4M
Bhattacharyya
2011
M16M
Bhattacharyya, Kundu
and Sanyal, 2011
UHS
PBS
Maciak, Ponniah and
sharma, 2005
Maciak, Ponniah and
sharma, 2005
Zaturenskiy, 2013
BF
Atoum et al., 2011a
 High capacity.
 Simple
BAF
Atoum et al., 2011b
 Low capacity.
SSAS
Atoum et al., 2013
 High capacity
and security
Weakness
 Good capacity
and security but
can be improved.
 Good capacity
and security but
can be improved.
 Simple
 Low imperceptibility and
robustness.
 Simple
 Not all MP3 contains
padding stuffing, just
constant bit rate.
 Low security and capacity.
 Low security.
 Using cryptography.
 Low imperceptibility and
robustness.
 Low security and capacity.
 Low security.
 Using cryptography.
 Don’t have message
integrity checking.
EVALUATION METHODS (STEGANALYSIS):
The evaluation method (steganalysis) aims to analyze a stego-object and detect if this stego-object
contains secret data or exposed to any change or it is a pure cover that has not been manipulated.
Steganalysis methods can be divided into two main groups: active and passive. In passive method, there is
no change in the cover after applying an attack, where the presence or the absence of hidden data is only
considered. While in active method, a modified version can destroy the message or even extract the data
[23].
Steganalysis could be a targeted steganalysis or a blind steganalysis. Targeted steganalysis breaks a
specific known steganography embedding scheme. Blind steganalysis attempts to detect the
steganography presence without a previous knowledge of the used algorithm. Technical approaches are
needed to scan the cover for suspicious properties or detecting hidden messages. Changes in size, file
format, colour palette or last modified timestamp may indicate a hidden message presence, but this is not
always true in all cases. Statistical analysis is one of the common techniques used for scanning image. In
this sub processes discussed and explain four evaluations methods: PSNR, Pearson correlation coefficient
and BER.
Peak signal-to-noise ratio (PSNR) is the ratio between a signal's maximum power and the power of the
signal's noise. Engineers commonly use the PSNR to measure the quality of reconstructed signals that
have been compressed. Signals can have a wide dynamic range, so PSNR is usually expressed in decibels
(db), which is a logarithmic scale. The PSNR block calculates the peak signal-to-noise ratio between two
hosts. This ratio is commonly used for quality measurement between the original cover and Stego object.
The higher PSNR value indicates better quality of the cover [24].
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The most familiar measure of dependence between two quantities is the Pearson correlation coefficient
[26-29], or "Pearson's correlation." It is obtained by dividing the covariance of the two variables by the
product of their standard deviations. Karl Pearson developed the coefficient from a similar but slightly
different idea by Francis Galton. The Pearson correlation is +1 in the case of a perfect positive (increasing)
linear relationship (correlation), -1 in the case of a perfect decreasing (negative) linear relationship (anti
correlation) , and some value between -1 and 1 in all other cases, indicating the degree of linear
dependence between the variables. As it approaches zero there is less of a relationship (closer to
uncorrelated). The closer the coefficient is to either -1 or 1, the stronger the correlation between the
variables. If the variables are independent, Pearson's correlation coefficient is 0, but the converse is not
true because the correlation coefficient detects only linear dependencies between two variables.
The bit error rate or bit error ratio (BER) is the number of bit errors divided by the total number of
transferred bits during a studied time interval. BER is a unit less performance measure often expressed as
a percentage. The bit error probability pe is the expectation value of the BER. The BER can be considered
as an approximate estimate of the bit error probability. This estimate is accurate for a long time interval
and a high number of bit errors [30].
In telecommunication transmission, the BER is the percentage of bits that have errors relative to the
total number of bits received in a transmission, usually expressed as ten to a negative power. For example,
a transmission might have a BER of 10 to the minus 6, meaning that, out of 1,000,000 bits transmitted,
one bit was in error. The BER is an indication of how often data has to be retransmitted because of an
error. Too high a BER may indicate that a slower Data Rate would actually improve overall transmission
time for a given amount of transmitted data since the BER might be reduced, lowering the number of
packets that had to be resent [31].
EXPERIMENTAL RESULTS
The dataset will be used for analysis shown in the Table 2, we will use different size for cover audio file
and using 100KB for secret message size to evaluate all methods.
Table 2 Data Set
Name of genre
Time
Size
(Minute)
(MB)
Pop
4:00
2.75
rock
4:33
3.13
Blues
4:41
3.22
Hip-hop
5:27
3.74
Dance
6:12
4.26
Metal
6:28
4.40
According to the Table.3 below the results for SSAS methods is better than other methods results, this
because the method using scrambling techniques to prepare the secret message before embedding and
using randomly first byte chosen to begin embedding secret message. In addition, using different jump
equations to jump from previous byte was used to embed into next byte should be used to embed.
However, SSAS method is applying message integrity to check the secret message was altered after
extraction. Thus, other methods avoid this checking. UHBS, PBS and BAF are stopped to embed because
the capacity for the secret message is 100KB.Figure 3 and 4 shows the PSNR and BER results for Table.3
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Table 3 Experimental results
Genre name
Methods
M4M
M16M
BF
SSAS
Pop
PSNR
63.035
53.569
48.212
68.117
Corr
0.9949
0.9949
0.9199
1.000
BER
0.0132
0.0098
0.0212
0.0032
PSNR
63.601
50.184
48.650
68.794
Corr
0.9949
0.9949
0.9199
1.000
BER
0.0112
0.0091
0.0198
0.0029
PSNR
63.708
0.232
49.806
68.830
Corr
0.9969
0.9969
0.9398
1.000
BER
0.0092
0.0081
0.0175
0.0027
PSNR
64.390
51.019
49.3759
69.425
Corr
0.9979
0.9979
0.9398
1.000
BER
0.0091
0.0074
0.0169
0.0017
PSNR
64.986
51.523
49.651
70.050
Corr
0.9997
0.9997
0.9449
1.000
BER
0.0087
0.0070
0.0145
0.0015
PSNR
65.117
1.667
49.748
70.142
Corr
0.9997
0.9997
0.9454
1.000
BER
0.0081
0.0067
0.0142
0.0011
Rock
Blues
Hip-hop
Dance
Metal
Figure 3: PSNR Results
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Editors: Gurpreet Dhillon and Spyridon Samonas
Figure 4: Bit Error Rate results
Conclusion
This paper concluded the comparison between different methods which that using MP3 steganography
techniques. The experimental results show that the SSAS method result is better than other methods
results. A test is made on various MP3 files which include different size and time. Different measurement
methods are used to evaluate the methods. PSNR, BER and correlation are three critical factors to
evaluate the methods. In the future, we can also extend SSAS method to add authentication code to prove
the secret message is sent by the right person.
REFERENCES
[1] Lentij J. (2000), Steganographic Methods, Department Of Control Engineering And Information
Technology, Budapest University. Periodica Poltechnica Ser. El. Eng. Vol.44, No. 3–4, P. 249–258.
[2] Katzenbeisser S., Peticotas F. (2000), Information Hiding Techniques For Steganography And Digital
Watermarking, Artech House Inc.
[3] Petitcolas F.A, Anderson R.J., Kuhn M.G. (1999), Information Hiding – A Survey, IEEE, Special Issue
On Protection Of Multimedia Content: 1062-1078.
[4] Cacciaguerra S., Ferretti S.(2002), Data Hiding: Steganography And Copyright Marking, Department
Of Computer Science, University Of Bologna, Italy.
[5] Nedeljko C. (2004). Algorithms for Audio Watermarking and Steganography. Acta Universitatis
Ouluensis. Series C.
[6] Andres G. (2002). Measuring and Evaluating Digital Watermarks in Audio files. Washington Dc.
[7] Supurovic P. (1998), MPEG Audio Compression Basics.
[8] M. Nilsson (2000), ID3 Tag Version 2.4.0 - Main Structure.
[9] L. Maciak And M. Ponniah And R. Sharma (2005), MP3 Steganography.
[10]Strnad Peter, Gingold Peter (1998), Lyrics3 Tag V2.00.
[11] M. Nilsson (2000), The Private Life Of MP3 Frames.
[12] Chan, P. (2011). Secret Sharing in Audio Steganography. Industrial Research.
[13] Deng, K., Tian, Y., Yu, X., Niu, X., Yang, Y., & Technology, S. (2010). Steganalysis of the MP3
Steganographic Algorithm Based on Huffman Coding. Test, (1), 79-82.
[14] Atoum, M. S., Ibrahim, S., Sulong,G. & Ahmed, A. (2012). MP3 Steganography: Review. Journal of
Computer Science issues, 9(6).
[15] Bhattacharyya, S., Kundu, A., Chakraborty, K., & Sanyal, G. (2011). Audio Steganography Using Mod
4 Method. Computing, 3(8), 30-38.
[16] Arko Kundu, Kaushik Chakraborty and Souvik Bhattacha-ryya (2011),Data Hiding in Images Using
Mod 16 Method, In the Proceedings of ETECE.
[17] Bhattacharyya, S, A Novel Audio Steganography Technique by M16MA (2011). International Journal,
30(8), 26-34.
[18] Mikhail Zaturenskiy (2009), Behind The Music: MP3 steganography.
[19] Atoum, M. S., Rababah, O. A. A.-, & Al-attili, A. I. (2011). New Technique for Hiding Data in Audio
File. Journal of Computer Science, 11(4), 173-177.
[20] Atoum, M. S., Suleiman, M., Rababaa, A., Ibrahim, S., & Ahmed, A. (2011). A Steganography Method
Based on Hiding secrete data in MPEG / Audio Layer III. Journal of Computer Science, 11(5), 184-188.
Information Institute Conferences, Las Vegas, NV, May 21-23, 2014
9
Atoum
[21] Atoum, M. S., Ibrahim, S., Sulong, G., & Ahmed, A. (2013).New Secure Scheme in Audio
Steganography (SSAS). Australian Journal of Basic and Applied Sciences, 7(6), 250–256.
[22] Atoum, M. S., Ibrahim, S., Sulong, G., & Zamani.M. (2014). A New Scheme for Audio Steganography
Using Message Integrity, Journal of Convergence Information Technology, 8(14), 35-44.
[23] Curran, K. and Devitt, J. M. (2008). Image Analysis for Online Dynamic Steganography Detection.
Computer and Information Science, 1(3), 32-42.
[24] Shirali S., Manzuri-Shalmani M.T. (2007). Adaptive Wavelet Domain Audio Steganography with
High Capacity and Low Error Rate. International Conference on Information and Emerging Technologies.
25-29.
[25] Shih, F. Y. and Edupuganti, V. G. (2009). A Differential Evolution Based Algorithm for Breaking the
Visual Steganalytic System. Soft Computing. Volume (13), 345-353.
[26] S. Dowdy and S. Wearden (1983), Statistics for research. Wiley.ISBN 0471086029, page 230,
[27] M. A. Jaro (1989), Advances in record linking methodology as applied to the 1985 census of tampa
florida. Journal of the American Statistical Society. 84:414–420.
[28] M. A. Jaro (1995), Probabilistic linkage of large public health data file. Statistics in Medicine 14 (57)., pages 491–498.
[29] W. E. Winkler (1999), The state of record linkage and current research problems. Statistics of Income
Division, Internal Revenue Service Publication R99/04.
[30] Harsh V., Ramanpreet K., Raman K. (2009). Random Sample Audio Watermarking Algorithm for
Compressed Wave Files. International Journal of Computer Science and Network Security, Volume (9).
[31] Andres G. (2002). Measuring and Evaluating Digital Watermarks in Audio Files. Washington DC.
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