2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017)

Experimental evaluation of encoding parameters of
MPEG-4 ALS for high-resolution audio
Shota Amada∗ , Yutaka Kamamoto† , Noboru Harada† , Ryosuke Sugiura† ,Takehiro Moriya† , Shoji Makino∗ and Takeshi Yamada∗∗ University of Tsukuba, Ibaraki, Japan† NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation. Kanagawa, Japan

Email:amada@mmlab.cs.tsukuba.ac.jp{kamamoto.yutaka, harada.noboru, sugiura.ryosuke, moriya.takehiro}@lab.ntt.co.jp
maki@tara.tsukuba.ac.jp takeshi@cs.tsukuba.ac.jp
Abstract—This paper describes experimental evaluations of
encoding parameters that are appropriate for MPEG-4 Audio Lossless Coding (ALS) to compress high-resolution audio.
MPEG-4 ALS Simple Proﬁle deﬁnes the values of encoding
parameters, such as the maximum sampling frequency andquantization bit depth, for making it easier to implement in
the receiving applications. However, ALS Simple Proﬁle does not
deﬁne values for 96-kHz high-resolution audio. Therefore, we
propose a range of values for 96-kHz high-resolution audio byextending the ALS Simple proﬁle and evaluating its performance.

I. I NTRODUCTION
According to the Japan Electronics and Information Technology Industries Association (JEITA), high-resolution audio
is deﬁned as high quality digital audio of which sampling
frequency or quantization bit depth exceeds the compact disc(CD) speciﬁcation and both are equal to or higher than the
CD speciﬁcation [1]. The bit-rate or storage size of the highresolution audio is several times that of the CD speciﬁcation
audio of the same recording time. General music CDs of
700-MB (700×1000×1000-byte) capacity can store about 66
minutes of CD speciﬁcation audio, but same capacity canstore only about 20 minutes of high-resolution audio with
96-kHz sampling rate and 24-bit quantization bit depth. For
this reason, the needs for compression is increasing. However
lossy compression such as MPEG-1/2 Audio Layer-3 (mp3)and MPEG-2/4 Advanced Audio Coding (AAC) makes digital
distortion and decrease the sound quality. Lossy coding reducehigh frequency components which humans hardly hear for
reducing total code length. The high-frequency components
are important for the people who select the high-resolution
audio, it should not be omitted. If further processing is
performed after lossy encoding, the distortion is emphasized
and the loss is perceived in some case. Therefore lossy coding
is inappropriate for compressing high-resolution audio andlossless compression is appropriate to maintain high soundquality of high-resolution audio.
Moving Picture Experts Group (MPEG), an international
standardization organization dealing with moving images and978-1-5090-4045-2/17/$31.00 ©2017 IEEE

audio data, has standardized MPEG-4 Audio Lossless Coding(ALS) as a lossless compression method of audio signals [2]–[4]. MPEG-4 ALS can handle many types of input signals
including high-resolution audio such as one with sampling
frequency up to about 4 GHz, quantization bit number up
to 32 bit and up to 65536 channels. MPEG-4 ALS Simple
Proﬁle (Table I) deﬁnes the upper limit of parameters suchas sampling frequency, quantization bit depth and number ofchannels for making it easier to implement in the receiving
device compared to ALS without any proﬁles.
ALS Simple Proﬁle has not deﬁned these limits of parameters for high-resolution audio yet. Referring to the MPEG-4
ALS Simple Proﬁle, for 48 kHz signals, maximum numberof samples per frame is 4096 and maximum prediction orderis 15. As shown in Fig. 1, when the sampling frequency isdoubled to 96 kHz, doubling maximum number of samples
per frame to 8192 and maximum prediction order to 31
makes it possible to process 96-kHz signals with the sametime window as 48-kHz signals. Therefore, we verify thecompression performance with these values of parameters andpropose appropriate values of parameters for the 96-kHz highresolution audio.
TABLE IL EVEL FOR THE MPEG-4 ALS S IMPLE P ROFILE(BS: B LOCK S WITCHING TOOL , MCC: M ULTI -C HANNEL C ODING TOOL )Level
Max. number of channels
Max. sampling rate [kHz]Max. word length [bit]Max. number of samples
per frame
Max. prediction orderMax. BS stages
Max. MCC stages

1
2
48
16

2
2
48
24

3
6
48
16

4
6
48
24

4096
15
3
1

4096
15
3
1

4096
15
3
1

4096
15
3
1

II. OVERVIEW OF MPEG-4 ALS
In MPEG-4 ALS, lossless compression is performed bylinear predictive analysis on input signals and expressing signal by prediction residual signals and partial auto-correlation577

2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017)








 
Fig. 1. Difference in number of samples at same time window.
           


  



   

 
 Fig. 2. Overview of MPEG-4 ALS encoder.

(PARCOR) coefﬁcients. Fig. 2 shows overview of the encoder.
There are trade-offs between the amount of information representing the prediction residual signal and PARCOR coefﬁcients. Eq. (1) denotes estimated total code length per frames
at the frame length is N and the prediction order is P, whereN
2
E(0) =
n=1 {x(n)} , x(n) (n = 1, 2, . . . , N ) is input
signal, ki (i = 1, 2, . . . , P ) are PARCOR coefﬁcients and γi
are the bits needed to represent the PARCOR coefﬁcients [5].




P
1
1
E(0)
C(P ) = N β + log2+
log2 (1 − ki2 )
2
N
2 i=1
+

P


γi

investigated the appropriate prediction order and frame length
when applying MPEG-4 ALS to high-resolution audio.
III. E XPERIMENTAL EVALUATION OF APPROPRIATEPARAMETERS

A. Experimental conditions
Table II shows the speciﬁcations of the audio that used in
the experiment. We prepared 15 audio data including jazz,orchestra, opera and so on. 48-kHz audio data are generated
by down-sampling 96-kHz audio data.
TABLE IIS PECIFICATIONS OF INPUT SOUND ITEMS .

(1)

Sampling rate [kHz]Number of channels
Word length [bit]Number of audio ﬁlesRecording time [s]File size (×106 )[byte]

i=1

Ignoring the ﬁrst two constant terms of Eq. (1), then Eq. (2)is obtained. Estimate code length from Eq. (2), select theprediction order considered to be optimum at the limit below
the maximum prediction order.

P 

N
2
log2 (1 − ki ) + γi
(2)C̃(P ) =2
i=1
If the prediction order is increased, the amount of information
for transmitting the prediction residual signals ( N2 log2 (1 −ki2 ) ) is reduced but the amount of information for transmitting
the PARCOR coefﬁcients ( γi ) is increased. The reverse isalso true. Therefore, it is necessary to consider an appropriate
prediction order that the total amount of information becomes
smaller. The frame length also affects the compression performance.
Thus, it is necessary to assign appropriate prediction orders
to each frame with appropriate frame length. Therefore, we

978-1-5090-4045-2/17/$31.00 ©2017 IEEE

48
2
24
15
30
8.64

96
2
24
15
30
17.28

B. Appropriate maximum prediction order and maximum
frame length
In this experiment, optimal prediction order is deﬁned asa prediction order by which the ﬁle size after encoding is
minimized. Fig. 3 shows the process of investigating theencoded ﬁlesize with each frame length and prediction order.
Perform this operation on 15 sound sources and ﬁnd the
optimum prediction orders at each frame length. The results
are averages from the results of 15 sound sources.
Figs. 4 and 5 show the histograms of the optimal prediction
orders that obtained by the exhaustive search within allowed578

2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017)

9

start

12

Frame Length 1024
Frame Length 2048
Frame Length 4096
Frame Length 8192
Top

N

Number of count [%]

8
256

P

¬1

apply
MPEG-4 ALS

¬1023

P

5
4

14

3
2

0

16
19

10

20

30

40

No

Number of count [%]

No
Yes

N

70

9

1

16384

60

Fig. 4. Histograms of optimal prediction orders for each frame length of
48-kHz signals.
Frame Length 1024
Frame Length 2048
Frame Length 4096
Frame Length 8192
Top

8

N

50

Prediction Order

Yes
P

6

1

save N, P and¬¬encoded filesize

P

7

N ✳¬2

end

range of the prediction order for each frame length of 48kHz and 96-kHz signals. Each ﬁgure plots the occurrence
frequencies of optimal orders and peaks in each frame length.
The peaks of the optimum prediction orders, for the 48-kHz
signals, is located near 15 in each frame length. In the 96-kHz
signals, peaks exceed 15 in every frame length and they arelocated less 31.
Figs. 6 and 7 is the graphs that superposed the curves ofcumulative percentage about occurrence frequencies of optimal orders on Figs. 4 and 5, right vertical axis is cumulative
percentage of the total number of occurrences. Tables. III
and IV show the cumulative percentages at 15-th and 31-thorder, 96-kHz and 48-kHz signal, each frame length. Increased
cumulative percentages by increasing 15-th to 31-th order are
greater at 96-kHz signals. Comparing the tables with the sametime window, 15-th order with 48-kHz signals and 31-th orderwith the 96-kHz signals, each frame length are (1024, 2048,
4096) and (2048, 4096, 8192), these cumulative percentage
are close. When the maximum prediction order is increased
to 31 at the 96-kHz signals, optimal prediction orders could
be handled at the same percentage as the maximum prediction
order is 15 at the 48-kHz signals.

978-1-5090-4045-2/17/$31.00 ©2017 IEEE

6
5

23

4
3
2

29

1

28

0

Fig. 3. Process of investigation the encoded ﬁlesize with each frame lengthand prediction order.

21

7

10

20

30

40

50

60

70

Prediction Order
Fig. 5. Histograms of optimal prediction orders for each frame length of
96-kHz signals.
TABLE IIIC UMULATIVE PERCENTAGES AT 48- K H Z SIGNALS .

Frame length
Cumulative percentages at 15-th order [%]Cumulative percentages at 31-th order [%]Increased percentages (15-th to 31-th) [%]

1024
54
76
22

2048
19
41
22

4096
6
16
10

8192
2
6
4

4096
3
20
17

8192
2
7
5

TABLE IV
C UMULATIVE PERCENTAGES AT 96- K H Z SIGNALS .

Frame length
Cumulative percentages at 15-th order [%]Cumulative percentages at 31-th order [%]Increased percentages (15-th to 31-th) [%]

1024
35
93
58

2048
10
57
47

Figs. 8 and 9 show the comparison of compressed ﬁlesize when we applied MPEG-4 ALS to each sampling frequency signal while changing the frame length and maximum
prediction order. The frame length with the minimum ﬁlesize were respectively 2048 and 4096 samples for 48-kHz
and 96-kHz signals. 8192-sample frame length is optimal579

2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017)

10

100

106
5.66

Frame length 1024
Frame length 2048
Frame length 4096
Frame length 8192

6

60

4

40

14

2

5.64

File size [byte]

80

Cumulative percentage[%]

Number of count[%]

12

8

20

16

10

5.62
5.6
5.58
5.56

19

0
0

max prediction order = 15
max prediction order = 31
max prediction order = 63
max prediction order = 1023

5.54

20

30

40

50

60

0

70

1024 2048

4096

8192

Prediction order

Frame length

Fig. 6. Cumulative percentages and histograms about optimal prediction
orders for each frame length of 48-kHz signals.

Fig. 8. The relationship between the encoded ﬁle size and frame length for
48-kHz signals.

10

106

100

Frame length 1024
Frame length 2048
Frame length 4096
Frame length 8192

21

6

80

60

23

4

40

29

2

10

20

30

8.25

8.2

20

8.15

28

0
0

max prediction order = 15
max prediction order = 31
max prediction order = 63
max prediction order = 1023

8.3

File size [byte]

8

Cumulative percentage[%]

Number of count[%]

8.35

40

50

60

0

1024 2048

70

Prediction orderFig. 7. Cumulative percentages and histograms about optimal prediction
orders for each frame length of 96-kHz signals.

in half of the audio ﬁles, so both 4096 and 8192-samples
frame length are appropriate for 96-kHz signals. MPEG-4
ALS adopts block length switching, which divides a frame
hierarchically into subblocks and can select and use optimal
combination of block lengths. Thus if the maximum value offrame length is set to 8192, 4096-samples frame length is alsoable to use. The compressed ﬁle size is decreased when the
maximum prediction order increased from 15 to 31. Ratio of
this improvement in 96-kHz signals is greater than 48-kHz
signal.
IV. C ONCLUSION
For high-resolution audio contents, increasing the maximum
prediction order and the maximum frame length can improvethe compression ratio, but on the other hand, the amount ofcalculation and buffer size required for decoding and encoding
increases. When MPEG-4 ALS was applied to high-resolution
audio with 96-kHz sampling frequency, the appropriate frame
length is 4096 or 8192. MPEG-4 ALS adopts block length978-1-5090-4045-2/17/$31.00 ©2017 IEEE

4096

8192

Frame length
Fig. 9. The relationship between the encoded ﬁle size and frame length for
96-kHz signals.

switching, so it is reasonable to set the maximum value offrame length to 8192. As shown in the experiment result, it
is expected that we can improve compression ratio more byextending the maximum prediction order to 31 for the 96-kHz
signal.
In conclusion, when applying MPEG-4 ALS Simple Proﬁleto 96-kHz high-resolution audio, the appropriate maximum
frame length is 8192-samples and the maximum prediction
order is 31.
R EFERENCES[1] 25JEITA-CP42, 2014.
http://home.jeita.or.jp/page ﬁle/20140328095728 rhsiN0Pz8x.pdf[2] ISO/IEC 14496-3:2009/Amd 3:2015, 2009 Information technology –Coding of audio-visual objects – Part 3: Audio[3] T. Liebechen, T. Moriya, N. Harada, Y. Kamamoto, and Y. Reznik”The MPEG-4 Audio Lossless Coding (ALS) Standard - Technology andApplications,” AES, 2005.
[4] T. Liebchen and Y. Reznik ”MPEG-4 ALSɿan emerging standard forlossless audio coding,” IEEE, Data Compression Conference, 2004.
[5] Y. Kamamoto, et al. ”Low-complexity PARCOR coefﬁcient quantizationand prediction order estimation designed for entropy coding of prediction
residuals,” 2013580