Develop Reference

How to analyse native memory on android?

Recently, my app gets large native memory after monkey, i can not reproduced manually, so i just can analyse through Android profiler.it shows 255264K memory in swap on native heap, but i can not see it in android profiler, so i refer to smap file. i can see a large malloc with 129M on swap.
Pss Private Private SwapPss Heap Heap Heap
Total Dirty Clean Dirty Size Alloc Free
------ ------ ------ ------ ------ ------ ------
Native Heap 75741 75496 220 255264 374656 331568 43087
Dalvik Heap 6606 5536 1032 0 18020 5748 12272
Dalvik Other 6844 6844 0 36
Stack 52 52 0 24
Ashmem 14 12 0 0
Gfx dev 17488 16652 836 0
Other dev 21 4 16 0
.so mmap 19382 224 14992 1063
.jar mmap 8 8 0 0
.apk mmap 19678 32 17360 20
.ttf mmap 7134 0 5752 0
.dex mmap 13703 0 8668 8
.oat mmap 2786 0 712 0
.art mmap 4541 3844 344 108
Other mmap 1997 4 1688 0
EGL mtrack 29388 29388 0 0
GL mtrack 19036 19036 0 0
Unknown 2227 2144 76 549
TOTAL 483718 159276 51696 257072 392676 337316 55359
9c800000-a4c00000 rw-p 00000000 00:00 0
[anon:libc_malloc]
Name: [anon:libc_malloc]
Size: 135168 kB
Rss: 5296 kB
Pss: 5296 kB
Shared_Clean: 0 kB
Shared_Dirty: 0 kB
Private_Clean: 0 kB
Private_Dirty: 5296 kB
Referenced: 4788 kB
Anonymous: 5296 kB
AnonHugePages: 0 kB
Shared_Hugetlb: 0 kB
Private_Hugetlb: 0 kB
Swap: 129872 kB
SwapPss: 129872 kB
KernelPageSize: 4 kB
MMUPageSize: 4 kB
Locked: 0 kB
now, my question is:
1.how can i get more information about this memory?
2.does 129M memory malloc at a time? how can application get so many momery for one time.
3.why this memory malloc on swap directly?
enter image description here

In order to get a detailed information about memory consumption, you can actually use "Android Profiler". You can get a detailed information about various components that may be using / storing memory of the application.

Android app consuming a lot of native heap space

I am trying to reduce the memory usage of my app.I started by fixing memory leaks in my code.This reduced the Dalvik heap space considerably but no difference in the native heap space allocated.
Is there a way I can reduce my native heap space consumption. If so, how should I go about doing it?
Heres what my app's heap dump looks like ""
Pss Private Private Swapped Heap Heap Heap
Total Dirty Clean Dirty Size Alloc Free
------ ------ ------ ------ ------ ------ ------
Native Heap 27240 27208 0 0 57344 24872 32471
Dalvik Heap 27138 26804 0 0 49430 41737 7693
Dalvik Other 624 624 0 0
Stack 924 924 0 0
Gfx dev 8738 5788 0 0
Other dev 16 0 16 0
.so mmap 833 332 124 0
.apk mmap 634 0 176 0
.ttf mmap 32 0 0 0
.dex mmap 12484 0 12480 0
.oat mmap 1146 0 124 0
.art mmap 1395 1212 4 0
Other mmap 44 4 0 0
Unknown 160 160 0 0
TOTAL 81408 63056 12924 0 106774 66609 40164
Objects
Views: 919 ViewRootImpl: 1
AppContexts: 3 Activities: 1
Assets: 214 AssetManagers: 214
Local Binders: 85 Proxy Binders: 22
Parcel memory: 24 Parcel count: 96
Death Recipients: 0 OpenSSL Sockets: 3
SQL
MEMORY_USED: 0
PAGECACHE_OVERFLOW: 0 MALLOC_SIZE: 0

reduce the memory when starting a Service(EGL mtrack too big)

First I declared the Service at manifest:
<service android:name=".TestService"
android:process=":test">
</service>
Then, I create a Service that does nothing:
public class TestService extends Service{
#Nullable
#Override
public IBinder onBind(Intent intent) {
return null;
}
}
I started a Service with
mContext.startService(new Intent(mContext, TestService.class));
in my Application,then I found the memory usage in 'Runing App' (get there by settings-> apps-> running) is 24M.And here is the meminfo I got:
adb shell dumpsys meminfo com.mypush:test
Applications Memory Usage (kB):
Uptime: 79955214 Realtime: 87129943
** MEMINFO in pid 2452 [com.mypush:test] **
Pss Private Private Swapped Heap Heap Heap
Total Dirty Clean Dirty Size Alloc Free
------ ------ ------ ------ ------ ------ ------
Native Heap 2508 2468 0 0 12288 4916 7371
Dalvik Heap 1354 956 0 0 22320 16969 5351
Dalvik Other 400 400 0 0
Stack 136 136 0 0
Gfx dev 628 628 0 0
Other dev 4 0 4 0
.so mmap 860 336 4 0
.apk mmap 29 0 0 0
.ttf mmap 9 0 0 0
.dex mmap 156 0 4 0
.oat mmap 191 0 0 0
.art mmap 564 268 0 0
Other mmap 36 4 0 0
EGL mtrack 13888 13888 0 0
GL mtrack 3272 3272 0 0
Unknown 152 152 0 0
TOTAL 24187 22508 12 0 34608 21885 12722
Objects
Views: 0 ViewRootImpl: 0
AppContexts: 3 Activities: 0
Assets: 3 AssetManagers: 3
Local Binders: 8 Proxy Binders: 13
Parcel memory: 3 Parcel count: 12
Death Recipients: 2 OpenSSL Sockets: 0
SQL
MEMORY_USED: 0
PAGECACHE_OVERFLOW: 0 MALLOC_SIZE: 0
I am running on Android 5.0/Nexus5, and found some apps used a Service use less memory than mine.So I want to know why?
Update
I have found that the EGL mtrack dumped is about 13M, it is not normal for a app that only has a empty Service.

Benchmarking the performance of an android device with swap enabled (swapon)

What factors do I need to look at when benchmarking the performance of an android device with swap enabled? and what applications are recommended to use if there are any?
Enabling swap requires the phone to be rooted and it's kernel to support swap. "a-swapper" is one of the applications I use for enabling swap, basically it launches commands to enable swap. The swap file or swap partition is located at the external SD card.
Link to "a-swapper" at google code:
http://code.google.com/p/a-swapper/

Following is a report of my paging tests on a Raspberry Pi (ARM CPU, 512 MB RAM, SD drive). A test program writes and reads increasing volumes of data, checking for correct results and measuring speed in MB/second. Data sizes reported are 350, 400, 420 and 600 MB. Speed was at about one tenth max at 420 MB and three times slower at 600 MB. Links are included to obtain the benchmarks and C source code (FREE for anyone to play with and no Ads on any pages). As with my other benchmarks, this can be converted for Android.
http://www.roylongbottom.org.uk/Raspberry%20Pi%20Stress%20Tests.htm#anchor18
The report also provides vmstat monitoring of memory used, swapped, cache size, drive I/O and CPU utilisation. At least on my Android tablet, I can run vmstat via a Terminal Emulator at the same time as executing benchmarks.
For Windows and Linux, I have an image processing benchmark that increasingly enlarges images, with writing and reading to a drive, rotating and scrolling (You can find details by Googling for bmpspeed results.htm and Linux SDL Image Processing Benchmarks). If there is a suitable photo editor for Android, you can do the same with that using manual timing, and possibly monitor with vmstat.
Paging Test Results
StressInt uses normal memory writing and reading functions. Part 1 writes then reads the specified space with six passes using different data patterns. Reading is at high speed using AND and OR to produce a sumcheck. Part 2 writes the patterns (not timed) and reads them for at least a minimum time, in this case there is only one read pass for each pattern. The four paging tests specified 350, 400, 420 and 600 MB on a Raspberry Pi that has 512 MB RAM, with the main drive being an SD card. Vmstat was run at the same time.
At 350 MB, there is no swapping, but cache and buffer sizes are reduced, slowing down the first write pass. At 400 KB, swapping in and out at start then full speed when sorted. At 420 MB, chaos, continuous data transfer to and from the drive, CPU waiting for I/O.
1. Commands Example
lxterminal -e ./stressInt KB 600000
vmstat 10 > vmburn4.txt
2. Results
MBytes Per Second At MB Data Size
MB 350 400 420 600
Write/Read No.
1 139 24 15 14
2 209 181 16 8
3 206 203 24 8
4 206 204 26 8
5 202 205 18 8
6 206 205 20 8
Write/Rd secs 19.6 48.4 204.9 460.7
Read No.
1 158 159 20 9
2 158 159 14 9
3 159 159 39 8
4 160 155 9 9
5 159 160 25 9
6 160 159 10 9
Total secs 85 125 1082 3085
vmstat si so KB swaps in and out, bi bo KB I/O in and out, wa = waiting for I/O
350 MB vmstat 10 second samples
KBytes KB KB/sec Per sec %
procs ----------memory---------- ---swap-- -----io---- -system-- ----cpu-----
r b swpd free buff cache si so bi bo in cs us sy id wa
0 0 0 314260 12340 56724 0 0 70 3 1123 232 19 5 76 0
1 1 4 8920 48 21844 0 0 37 10 1141 298 42 16 42 0
1 0 8 12392 64 18404 0 0 2 9 1161 89 99 1 0 0
1 0 8 12144 80 18704 0 0 30 6 1167 82 99 1 0 0
1 0 8 11896 88 18868 0 0 16 2 1157 71 99 1 0 0
1 0 8 11764 96 18972 0 0 10 7 1163 71 99 1 0 0
1 0 8 11772 104 18972 0 0 0 3 1152 61 100 0 0 0
1 0 8 11772 112 18972 0 0 0 3 1153 65 100 0 0 0
1 0 8 11772 120 18972 0 0 0 4 1154 68 100 0 0 0
1 0 8 11772 128 18972 0 0 0 3 1153 64 100 0 0 0
0 0 8 362344 136 21384 0 0 239 5 1194 294 22 4 73 1
400 MB
procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu-----
r b swpd free buff cache si so bi bo in cs us sy id wa
0 0 8 355220 924 26480 0 0 63 3 1125 236 24 4 72 0
1 5 92368 8968 60 5464 10 9236 338 9245 1739 587 31 20 28 21
0 2 52492 9108 44 5092 4775 3802 6938 3807 3429 1169 10 22 0 68
1 2 71168 11236 44 4920 4654 8936 4929 8936 2428 1036 6 18 0 77
1 1 42216 9224 44 4788 4477 5600 5059 5602 3313 992 37 19 0 45
1 1 40948 11008 44 4932 143 0 591 3 1391 163 98 2 0 0
1 0 40924 12248 60 5032 15 0 33 6 1170 87 98 2 0 0
1 0 40912 12116 60 5228 2 0 21 0 1155 66 99 1 0 0
1 0 40912 12000 68 5228 0 0 0 3 1152 58 100 1 0 0
1 0 40912 12000 76 5260 3 0 6 3 1154 60 100 1 0 0
1 0 40892 12000 84 5260 0 0 0 3 1153 63 99 1 0 0
1 0 40704 11628 92 5260 34 0 34 3 1167 69 100 1 0 0
1 0 40700 11628 100 5260 0 0 0 3 1153 61 100 0 0 0
0 0 37956 401996 236 12804 474 0 1208 0 1626 229 89 5 3 3
0 0 36900 400392 244 13372 103 0 160 7 1125 180 6 2 91 1
420 MB Sample
procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu----
r b swpd free buff cache si so bi bo in cs us sy id wa
0 3 59316 8820 48 4212 4238 4269 5132 4272 3592 939 20 16 0 65
0 1 68268 11732 44 3400 4281 5112 4736 5114 3337 938 6 19 0 75
1 3 60804 8820 76 4428 4715 3860 5877 3864 3518 1007 13 17 0 70
1 1 56408 9948 44 2976 4710 4164 6948 4168 4389 1186 5 19 0 75
2 2 70864 11704 44 2068 3975 6458 4908 6461 3854 1021 7 14 0 79
Following are results on 64 bit Windows systems, essentially from same C code as on Raspberry Pi but using one write/read pass. For these tests the benchmark was run with increasing data demands up to 5, 8 and 14 GB on the three systems.
64 Bit IntBurn64 64 Bit IntBurn64 64 Bit IntBurn64
CPU Athlon 64 Core 2 Duo Phenom II
MHz 2210 2400 3000
RAM MB 1024 4096 8192
Windows XP x64 64-Bit Vista 64-Bit Windows 7
Disk W/R
MB/sec 55 55 92
KB Secs MB/sec KB Secs MB/sec KB Secs MB/sec
100000 2041 100000 3393 100000 5146
800000 1 1976 2500000 2 2868 2000000 1 4900
850000 23 77 3000000 2 2878 3000000 1 4658
900000 58 32 3100000 2 2847 3500000 2 4651
920000 61 31 3200000 2 2899 4000000 2 4488
930000 91 21 3300000 3 2698 4500000 2 4489
940000 96 20 3400000 3 2610 5000000 2 4477
950000 93 21 3500000 7 1075 5500000 3 4166
960000 89 22 3600000 10 750 6000000 3 4051
970000 142 14 3700000 17 459 6500000 3 4036
980000 125 16 3800000 107 73 7000000 4 4078
990000 119 17 3900000 210 38 7500000 72 214
1000000 128 16 4000000 146 56 7600000 170 91
1100000 188 12 7700000 168 94
1200000 205 12 5000000 1024 10 7800000 230 69
1300000 266 10 7000000 652 22 7900000 239 68
1400000 358 8 7900000 770 21 8000000 227 72
8000000 N/A 9000000 697 26
2000000 683 6 10000000 1231 17
2100000 14000000 2742 10
5000000 1707 6 15000000 N/A
BMPSpeed Benchmark generates BMP files up to 512 MB. It measures speed of saving, loading, scrolling, rotating and editing/enlarging of 0.5, 1, 2, 4 etc. MB files upwards. Memory used is up to 2.5 times image size. The original had to be modifies for a Windows XP as 1.25 GB of sequential memory space could not be allocated. The first example below reflects paging at 256 MB but some memory would be cleared for a rerun. A second problem arises on later systems, with more graphics RAM, where fast BitBlt copying can be used at larger image sizes and this requires far more space than the slower StretchDIBits method.
I might produce a new 64 bit version to see if I can bust my new benchmarking toy with 32 GB RAM.
BMPSpeed Results
2.08 GHz CPU, 512 MB RAM, fast disk, slow GeForce graphics
Input Enlarge Save Load Scroll Scroll Rotate Use
Image Display Display /Repeat Overall 90 deg Fast
Mbytes Secs Secs Secs msecs MB/Sec Secs BitBlt
0.5 0.05 0.01 0.03 0.7 992.8 0.04 3
1.0 0.06 0.02 0.05 1.3 1013.2 0.06 3
2.0 0.08 0.03 0.12 2.3 1019.8 0.09 3
4.0 0.11 0.06 0.17 2.9 1032.4 0.15 3
8.0 0.15 0.14 0.43 11.4 262.7 0.25 3
16.0 0.24 0.29 0.51 11.4 262.7 0.81 3
32.0 0.45 0.61 0.88 11.4 262.5 1.10 3
64.0 0.55 1.31 1.49 41.4 72.2 2.79 0
128.0 0.97 2.50 2.83 53.9 55.5 6.21 0
256.0 73.02 88.77 14.84 109.7 27.3 86.60 0
512.0 82.93 20.70 89.05 842.4 3.5 67.98 0
2.4 GHz Core 2 Duo with 4 GB RAM and 64 Bit Vista, fast GeForce
Input Enlarge Save Load Scroll Scroll Rotate Use
Image Display Display /Repeat Overall 90 deg Fast
Mbytes Secs Secs Secs msecs MB/Sec Secs BitBlt
0.5 0.05 0.01 0.05 0.1 4748.4 0.02 3
1.0 0.05 0.02 0.08 0.3 4463.6 0.03 3
2.0 0.07 0.02 0.11 1.1 2475.2 0.04 3
4.0 0.09 0.03 0.19 2.4 1866.0 0.06 3
8.0 0.13 0.08 0.31 2.9 1765.0 0.10 3
16.0 0.20 0.24 0.48 2.7 1832.5 0.17 3
32.0 0.26 0.52 0.78 2.9 1741.2 0.28 3
64.0 0.39 1.08 1.38 2.9 1760.0 0.52 3
128.0 0.68 2.37 2.63 2.9 1740.3 1.03 3
256.0 1.35 4.62 5.38 3.1 1645.6 4.39 3
512.0 27.91 13.05 10.59 3.2 1595.6 57.11 3

Terrible voice to text detection with pocketsphinx

I followed the tutorial here for getting pocketsphinx up and running on Android. I ran the application on a Samsung Galaxy 2 and started speaking.
The problem is that the performance is terrible. I might say "Hello" and the phone will output "That" on the screen. It is definitely detecting noise through the mic because there is output only when I am speaking. I think there must be something wrong with my setup.
Does anyone know why I am getting such bad performance?
public RecognizerTask() {
pocketsphinx
// .setLogfile("/sdcard/Android/data/edu.cmu.pocketsphinx/pocketsphinx.log");
.setLogfile("/mnt/sdcard/edu.cmu.pocketsphinx/pocketsphinx.log");
Config c = new Config();
/*
* In 2.2 and above we can use getExternalFilesDir() or whatever it's
* called
*/
/*
c.setString("-hmm",
"/sdcard/Android/data/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k");
c.setString("-dict",
"/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.dic");
c.setString("-lm",
"/sdcard/Android/data/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.DMP");
*/
c.setString("-hmm", "/mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k");
c.setString("-dict", "/mnt/sdcard/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.dic");
c.setString("-lm", "/mnt/sdcard/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.DMP");
c.setString("-rawlogdir", "/mnt/sdcard/edu.cmu.pocketsphinx"); // Only use it to store the audio
/*
c.setString("-hmm",
"/sdcard/Android/data/edu.cmu.pocketsphinx/hmm/zh/tdt_sc_8k");
c.setString("-dict",
"/sdcard/Android/data/edu.cmu.pocketsphinx/lm/zh_TW/mandarin_notone.dic");
c.setString("-lm",
"/sdcard/Android/data/edu.cmu.pocketsphinx/lm/zh_TW/gigatdt.5000.DMP");
*/
//c.setString("-rawlogdir", "/sdcard/Android/data/edu.cmu.pocketsphinx");
c.setFloat("-samprate", 8000.0);
c.setInt("-maxhmmpf", 2000);
c.setInt("-maxwpf", 10);
c.setInt("-pl_window", 2);
c.setBoolean("-backtrace", true);
c.setBoolean("-bestpath", false);
this.ps = new Decoder(c);
this.audio = null;
this.audioq = new LinkedBlockingQueue<short[]>();
this.use_partials = false;
this.mailbox = Event.NONE;
}
pocketsphinx.log
INFO: cmd_ln.c(691): Parsing command line:
Current configuration:
[NAME] [DEFLT] [VALUE]
-agc none none
-agcthresh 2.0 2.000000e+00
-alpha 0.97 9.700000e-01
-ascale 20.0 2.000000e+01
-aw 1 1
-backtrace no no
-beam 1e-48 1.000000e-48
-bestpath yes yes
-bestpathlw 9.5 9.500000e+00
-bghist no no
-ceplen 13 13
-cmn current current
-cmninit 8.0 8.0
-compallsen no no
-debug 0
-dict
-dictcase no no
-dither no no
-doublebw no no
-ds 1 1
-fdict
-feat 1s_c_d_dd 1s_c_d_dd
-featparams
-fillprob 1e-8 1.000000e-08
-frate 100 100
-fsg
-fsgusealtpron yes yes
-fsgusefiller yes yes
-fwdflat yes yes
-fwdflatbeam 1e-64 1.000000e-64
-fwdflatefwid 4 4
-fwdflatlw 8.5 8.500000e+00
-fwdflatsfwin 25 25
-fwdflatwbeam 7e-29 7.000000e-29
-fwdtree yes yes
-hmm
-input_endian little little
-jsgf
-kdmaxbbi -1 -1
-kdmaxdepth 0 0
-kdtree
-latsize 5000 5000
-lda
-ldadim 0 0
-lextreedump 0 0
-lifter 0 0
-lm
-lmctl
-lmname default default
-logbase 1.0001 1.000100e+00
-logfn
-logspec no no
-lowerf 133.33334 1.333333e+02
-lpbeam 1e-40 1.000000e-40
-lponlybeam 7e-29 7.000000e-29
-lw 6.5 6.500000e+00
-maxhmmpf -1 -1
-maxnewoov 20 20
-maxwpf -1 -1
-mdef
-mean
-mfclogdir
-min_endfr 0 0
-mixw
-mixwfloor 0.0000001 1.000000e-07
-mllr
-mmap yes yes
-ncep 13 13
-nfft 512 512
-nfilt 40 40
-nwpen 1.0 1.000000e+00
-pbeam 1e-48 1.000000e-48
-pip 1.0 1.000000e+00
-pl_beam 1e-10 1.000000e-10
-pl_pbeam 1e-5 1.000000e-05
-pl_window 0 0
-rawlogdir
-remove_dc no no
-round_filters yes yes
-samprate 16000 1.600000e+04
-seed -1 -1
-sendump
-senlogdir
-senmgau
-silprob 0.005 5.000000e-03
-smoothspec no no
-svspec
-tmat
-tmatfloor 0.0001 1.000000e-04
-topn 4 4
-topn_beam 0 0
-toprule
-transform legacy legacy
-unit_area yes yes
-upperf 6855.4976 6.855498e+03
-usewdphones no no
-uw 1.0 1.000000e+00
-var
-varfloor 0.0001 1.000000e-04
-varnorm no no
-verbose no no
-warp_params
-warp_type inverse_linear inverse_linear
-wbeam 7e-29 7.000000e-29
-wip 0.65 6.500000e-01
-wlen 0.025625 2.562500e-02
INFO: cmd_ln.c(691): Parsing command line:
\
-nfilt 20 \
-lowerf 1 \
-upperf 4000 \
-wlen 0.025 \
-transform dct \
-round_filters no \
-remove_dc yes \
-svspec 0-12/13-25/26-38 \
-feat 1s_c_d_dd \
-agc none \
-cmn current \
-cmninit 56,-3,1 \
-varnorm no
Current configuration:
[NAME] [DEFLT] [VALUE]
-agc none none
-agcthresh 2.0 2.000000e+00
-alpha 0.97 9.700000e-01
-ceplen 13 13
-cmn current current
-cmninit 8.0 56,-3,1
-dither no no
-doublebw no no
-feat 1s_c_d_dd 1s_c_d_dd
-frate 100 100
-input_endian little little
-lda
-ldadim 0 0
-lifter 0 0
-logspec no no
-lowerf 133.33334 1.000000e+00
-ncep 13 13
-nfft 512 512
-nfilt 40 20
-remove_dc no yes
-round_filters yes no
-samprate 16000 8.000000e+03
-seed -1 -1
-smoothspec no no
-svspec 0-12/13-25/26-38
-transform legacy dct
-unit_area yes yes
-upperf 6855.4976 4.000000e+03
-varnorm no no
-verbose no no
-warp_params
-warp_type inverse_linear inverse_linear
-wlen 0.025625 2.500000e-02
INFO: acmod.c(246): Parsed model-specific feature parameters from /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/feat.params
INFO: feat.c(713): Initializing feature stream to type: '1s_c_d_dd', ceplen=13, CMN='current', VARNORM='no', AGC='none'
INFO: cmn.c(142): mean[0]= 12.00, mean[1..12]= 0.0
INFO: acmod.c(167): Using subvector specification 0-12/13-25/26-38
INFO: mdef.c(517): Reading model definition: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/mdef
INFO: mdef.c(528): Found byte-order mark BMDF, assuming this is a binary mdef file
INFO: bin_mdef.c(336): Reading binary model definition: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/mdef
INFO: bin_mdef.c(513): 50 CI-phone, 143047 CD-phone, 3 emitstate/phone, 150 CI-sen, 5150 Sen, 27135 Sen-Seq
INFO: tmat.c(205): Reading HMM transition probability matrices: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/transition_matrices
INFO: acmod.c(121): Attempting to use SCHMM computation module
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/means
INFO: ms_gauden.c(292): 1 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/variances
INFO: ms_gauden.c(292): 1 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(354): 0 variance values floored
INFO: s2_semi_mgau.c(903): Loading senones from dump file /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/sendump
INFO: s2_semi_mgau.c(927): BEGIN FILE FORMAT DESCRIPTION
INFO: s2_semi_mgau.c(1022): Using memory-mapped I/O for senones
INFO: s2_semi_mgau.c(1296): Maximum top-N: 4 Top-N beams: 0 0 0
INFO: phone_loop_search.c(105): State beam -230231 Phone exit beam -115115 Insertion penalty 0
INFO: dict.c(317): Allocating 10319 * 20 bytes (201 KiB) for word entries
INFO: dict.c(332): Reading main dictionary: /mnt/sdcard/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.dic
INFO: dict.c(211): Allocated 44 KiB for strings, 69 KiB for phones
INFO: dict.c(335): 6212 words read
INFO: dict.c(341): Reading filler dictionary: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/noisedict
INFO: dict.c(211): Allocated 0 KiB for strings, 0 KiB for phones
INFO: dict.c(344): 11 words read
INFO: dict2pid.c(396): Building PID tables for dictionary
INFO: dict2pid.c(404): Allocating 50^3 * 2 bytes (244 KiB) for word-initial triphones
INFO: dict2pid.c(131): Allocated 30200 bytes (29 KiB) for word-final triphones
INFO: dict2pid.c(195): Allocated 30200 bytes (29 KiB) for single-phone word triphones
INFO: ngram_model_arpa.c(77): No \data\ mark in LM file
INFO: ngram_model_dmp.c(142): Will use memory-mapped I/O for LM file
INFO: ngram_model_dmp.c(196): ngrams 1=5001, 2=436879, 3=418286
INFO: ngram_model_dmp.c(242): 5001 = LM.unigrams(+trailer) read
INFO: ngram_model_dmp.c(288): 436879 = LM.bigrams(+trailer) read
INFO: ngram_model_dmp.c(314): 418286 = LM.trigrams read
INFO: ngram_model_dmp.c(339): 37293 = LM.prob2 entries read
INFO: ngram_model_dmp.c(359): 14370 = LM.bo_wt2 entries read
INFO: ngram_model_dmp.c(379): 36094 = LM.prob3 entries read
INFO: ngram_model_dmp.c(407): 854 = LM.tseg_base entries read
INFO: ngram_model_dmp.c(463): 5001 = ascii word strings read
INFO: ngram_search_fwdtree.c(99): 457 unique initial diphones
INFO: ngram_search_fwdtree.c(147): 0 root, 0 non-root channels, 27 single-phone words
INFO: ngram_search_fwdtree.c(186): Creating search tree
INFO: ngram_search_fwdtree.c(191): before: 0 root, 0 non-root channels, 27 single-phone words
INFO: ngram_search_fwdtree.c(326): after: max nonroot chan increased to 13439
INFO: ngram_search_fwdtree.c(338): after: 457 root, 13311 non-root channels, 26 single-phone words
INFO: ngram_search_fwdflat.c(156): fwdflat: min_ef_width = 4, max_sf_win = 25
INFO: cmd_ln.c(691): Parsing command line:
Current configuration:
[NAME] [DEFLT] [VALUE]
-agc none none
-agcthresh 2.0 2.000000e+00
-alpha 0.97 9.700000e-01
-ascale 20.0 2.000000e+01
-aw 1 1
-backtrace no no
-beam 1e-48 1.000000e-48
-bestpath yes yes
-bestpathlw 9.5 9.500000e+00
-bghist no no
-ceplen 13 13
-cmn current current
-cmninit 8.0 8.0
-compallsen no no
-debug 0
-dict
-dictcase no no
-dither no no
-doublebw no no
-ds 1 1
-fdict
-feat 1s_c_d_dd 1s_c_d_dd
-featparams
-fillprob 1e-8 1.000000e-08
-frate 100 100
-fsg
-fsgusealtpron yes yes
-fsgusefiller yes yes
-fwdflat yes yes
-fwdflatbeam 1e-64 1.000000e-64
-fwdflatefwid 4 4
-fwdflatlw 8.5 8.500000e+00
-fwdflatsfwin 25 25
-fwdflatwbeam 7e-29 7.000000e-29
-fwdtree yes yes
-hmm
-input_endian little little
-jsgf
-kdmaxbbi -1 -1
-kdmaxdepth 0 0
-kdtree
-latsize 5000 5000
-lda
-ldadim 0 0
-lextreedump 0 0
-lifter 0 0
-lm
-lmctl
-lmname default default
-logbase 1.0001 1.000100e+00
-logfn
-logspec no no
-lowerf 133.33334 1.333333e+02
-lpbeam 1e-40 1.000000e-40
-lponlybeam 7e-29 7.000000e-29
-lw 6.5 6.500000e+00
-maxhmmpf -1 -1
-maxnewoov 20 20
-maxwpf -1 -1
-mdef
-mean
-mfclogdir
-min_endfr 0 0
-mixw
-mixwfloor 0.0000001 1.000000e-07
-mllr
-mmap yes yes
-ncep 13 13
-nfft 512 512
-nfilt 40 40
-nwpen 1.0 1.000000e+00
-pbeam 1e-48 1.000000e-48
-pip 1.0 1.000000e+00
-pl_beam 1e-10 1.000000e-10
-pl_pbeam 1e-5 1.000000e-05
-pl_window 0 0
-rawlogdir
-remove_dc no no
-round_filters yes yes
-samprate 16000 1.600000e+04
-seed -1 -1
-sendump
-senlogdir
-senmgau
-silprob 0.005 5.000000e-03
-smoothspec no no
-svspec
-tmat
-tmatfloor 0.0001 1.000000e-04
-topn 4 4
-topn_beam 0 0
-toprule
-transform legacy legacy
-unit_area yes yes
-upperf 6855.4976 6.855498e+03
-usewdphones no no
-uw 1.0 1.000000e+00
-var
-varfloor 0.0001 1.000000e-04
-varnorm no no
-verbose no no
-warp_params
-warp_type inverse_linear inverse_linear
-wbeam 7e-29 7.000000e-29
-wip 0.65 6.500000e-01
-wlen 0.025625 2.562500e-02
INFO: cmd_ln.c(691): Parsing command line:
\
-nfilt 20 \
-lowerf 1 \
-upperf 4000 \
-wlen 0.025 \
-transform dct \
-round_filters no \
-remove_dc yes \
-svspec 0-12/13-25/26-38 \
-feat 1s_c_d_dd \
-agc none \
-cmn current \
-cmninit 56,-3,1 \
-varnorm no
Current configuration:
[NAME] [DEFLT] [VALUE]
-agc none none
-agcthresh 2.0 2.000000e+00
-alpha 0.97 9.700000e-01
-ceplen 13 13
-cmn current current
-cmninit 8.0 56,-3,1
-dither no no
-doublebw no no
-feat 1s_c_d_dd 1s_c_d_dd
-frate 100 100
-input_endian little little
-lda
-ldadim 0 0
-lifter 0 0
-logspec no no
-lowerf 133.33334 1.000000e+00
-ncep 13 13
-nfft 512 512
-nfilt 40 20
-remove_dc no yes
-round_filters yes no
-samprate 16000 8.000000e+03
-seed -1 -1
-smoothspec no no
-svspec 0-12/13-25/26-38
-transform legacy dct
-unit_area yes yes
-upperf 6855.4976 4.000000e+03
-varnorm no no
-verbose no no
-warp_params
-warp_type inverse_linear inverse_linear
-wlen 0.025625 2.500000e-02
INFO: acmod.c(246): Parsed model-specific feature parameters from /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/feat.params
INFO: feat.c(713): Initializing feature stream to type: '1s_c_d_dd', ceplen=13, CMN='current', VARNORM='no', AGC='none'
INFO: cmn.c(142): mean[0]= 12.00, mean[1..12]= 0.0
INFO: acmod.c(167): Using subvector specification 0-12/13-25/26-38
INFO: mdef.c(517): Reading model definition: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/mdef
INFO: mdef.c(528): Found byte-order mark BMDF, assuming this is a binary mdef file
INFO: bin_mdef.c(336): Reading binary model definition: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/mdef
INFO: bin_mdef.c(513): 50 CI-phone, 143047 CD-phone, 3 emitstate/phone, 150 CI-sen, 5150 Sen, 27135 Sen-Seq
INFO: tmat.c(205): Reading HMM transition probability matrices: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/transition_matrices
INFO: acmod.c(121): Attempting to use SCHMM computation module
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/means
INFO: ms_gauden.c(292): 1 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/variances
INFO: ms_gauden.c(292): 1 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(294): 256x13
INFO: ms_gauden.c(354): 0 variance values floored
INFO: s2_semi_mgau.c(903): Loading senones from dump file /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/sendump
INFO: s2_semi_mgau.c(927): BEGIN FILE FORMAT DESCRIPTION
INFO: s2_semi_mgau.c(1022): Using memory-mapped I/O for senones
INFO: s2_semi_mgau.c(1296): Maximum top-N: 4 Top-N beams: 0 0 0
INFO: phone_loop_search.c(105): State beam -230231 Phone exit beam -115115 Insertion penalty 0
INFO: dict.c(317): Allocating 10319 * 20 bytes (201 KiB) for word entries
INFO: dict.c(332): Reading main dictionary: /mnt/sdcard/edu.cmu.pocketsphinx/lm/en_US/hub4.5000.dic
INFO: dict.c(211): Allocated 44 KiB for strings, 69 KiB for phones
INFO: dict.c(335): 6212 words read
INFO: dict.c(341): Reading filler dictionary: /mnt/sdcard/edu.cmu.pocketsphinx/hmm/en_US/hub4wsj_sc_8k/noisedict
INFO: dict.c(211): Allocated 0 KiB for strings, 0 KiB for phones
INFO: dict.c(344): 11 words read
INFO: dict2pid.c(396): Building PID tables for dictionary
INFO: dict2pid.c(404): Allocating 50^3 * 2 bytes (244 KiB) for word-initial triphones
INFO: dict2pid.c(131): Allocated 30200 bytes (29 KiB) for word-final triphones
INFO: dict2pid.c(195): Allocated 30200 bytes (29 KiB) for single-phone word triphones
INFO: ngram_model_arpa.c(77): No \data\ mark in LM file
INFO: ngram_model_dmp.c(142): Will use memory-mapped I/O for LM file
INFO: ngram_model_dmp.c(196): ngrams 1=5001, 2=436879, 3=418286
INFO: ngram_model_dmp.c(242): 5001 = LM.unigrams(+trailer) read
INFO: ngram_model_dmp.c(288): 436879 = LM.bigrams(+trailer) read
INFO: ngram_model_dmp.c(314): 418286 = LM.trigrams read
INFO: ngram_model_dmp.c(339): 37293 = LM.prob2 entries read
INFO: ngram_model_dmp.c(359): 14370 = LM.bo_wt2 entries read
INFO: ngram_model_dmp.c(379): 36094 = LM.prob3 entries read
INFO: ngram_model_dmp.c(407): 854 = LM.tseg_base entries read
INFO: ngram_model_dmp.c(463): 5001 = ascii word strings read
INFO: ngram_search_fwdtree.c(99): 457 unique initial diphones
INFO: ngram_search_fwdtree.c(147): 0 root, 0 non-root channels, 27 single-phone words
INFO: ngram_search_fwdtree.c(186): Creating search tree
INFO: ngram_search_fwdtree.c(191): before: 0 root, 0 non-root channels, 27 single-phone words
INFO: ngram_search_fwdtree.c(326): after: max nonroot chan increased to 13439
INFO: ngram_search_fwdtree.c(338): after: 457 root, 13311 non-root channels, 26 single-phone words
INFO: ngram_search_fwdflat.c(156): fwdflat: min_ef_width = 4, max_sf_win = 25
And a link to the log file and .raw files
dl.dropbox.com/s/3dkueyz4wgx174z/pocketsphinx.zip?dl=1