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Updated 12k Word 16kHz Sphinx Model Available
User: guenter
Date: 2/15/2014 12:27 pm
Views: 11818
Rating: 2

Those following the audio tagging thread already know this, but here is the "official" announcement anyway:

Over the past few weeks I have (with a lot of help from this forum) computed an updated german voxforge model for CMU pocketsphinx (SVN trunk).

The model is available for download here:

http://goofy.zamia.org/voxforge/de/

Some statistics about this model (more in voxforge.html and audio-stats.txt):

  • 11902 words in dictionary
  • statistical language model included built using the German Parole Corpus
  • Sentence error rate 6.9%, word error rate 1.9%
  • 2276.39min of audio material used
the model is currently dominated by two speakers (ralfherzog and me :o) ) so do not expect such low error rates for other speakers just now (the model should be usable for command and control applications for other speakers, though).
Please help improving the model - simply by uploading more audio material to VoxForge. I intend to update the model from time to time when new material becomes available (yes, I will also continue to produce material myself but help from others is definitely needed).
All scripts used to generate the model along with some documentation is available on github:
https://github.com/gooofy/voxforge

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: Visitor
Date: 2/17/2014 8:00 am
Views: 134
Rating: 0

Hallo

May i request you to share the audio files 16khz with us?

I would require the files for recognizing numbers.. I can add them to my systems.. Ofcourse i will add all generated audiofile samples for my acoustic model for others too ..

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: guenter
Date: 3/26/2014 5:17 pm
Views: 87
Rating: 0

sorry for my late response - I have finally found the time to pack and upload the remaining audio files I produced over the past weeks.

everything is available in voxforge / de / audio / main :

http://www.repository.voxforge1.org/downloads/de/Trunk/Audio/Main/16kHz_16bit/

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: Binh
Date: 3/6/2014 3:26 am
Views: 162
Rating: 0

Kleine Anmerkung.

In deinen Submissions sind eine Reihe von Fremdwörtern, wie Hidden Markov Modell. Obwohl sie praktisch natürlich zum deutschen Sprachgebrauch gehören führen Wörter wie "Hidden" auf unserem System zu gewissen Problemen. ( kleine Transitionmatrix Probleme).

Im allgmeinen sollte man fürs erste vermutlich keine Fremdwörter benutzen.Ansonsten . Good work :thumbsup:


Es exisitieren eine ganze Reihe von Papern im Versuch diese zu behandeln, aber ich glaube nicht das irgend eines davon bereits umgesetzt wurde.

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: guenter
Date: 3/26/2014 5:21 pm
Views: 112
Rating: 0

mir ist sehr unklar, warum solche woerter zu problemen fuehren - enthalten sie phoneme, die solche systeme sonst nicht kennen?

grundsaetzlich sollte es doch voellig egal sein, ob es sich um fremdwoerter handelt oder nicht - zumal gerade das deutsche ja recht arm an "eigenen" woertern ist (und selbst die sind ja oft lateinischen oder griechischen ursprungs ;) ) - mir ist nichtmal ganz klar, wie ein computer diese unterscheidung ueberhaupt treffen koennte.

wie dem auch seie - ich sehe im moment fuer mich keine moeglichkeit, ohne fremdwoerter auszukommen, weil ich in richtung eines dialogsystems plane, das moeglichst mit alltagssprache zurecht kommen soll und da gehoeren zumindest woerter wie "computer" und "handy" einfach dazu, auch wenn es fremdwoerter sind.

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: Binh
Date: 3/27/2014 3:38 am
Views: 309
Rating: 0

Es kommt sehr darauf an, welches Wörterbuch dahinter liegt.

Nehmen wir hier mal gleich das Beispiel Handy.

Lies es einmal deutsch und einmal englisch vor.


Sollte ich es ungefähr den wortlaut transcibieren würde ich "händi" nehmen .  Natürlich wissen Programme wie espeak das nicht und machen was anderes daraus. "Hand y" wäre eine Variante aber ich weiss es mometan nicht da die Kombination dy so gut wie gar nicht in deutschen nicht-fremdwörtern auftaucht.

Man müßte also erst die englischen Phonemereihe erstellen und diese dann in eine äquivalente deutsche Phonemreihe umwandeln.

You get my point. Solange man auch dein Wörterbuch mit übernimmt und du überall darauf geachtet hast, sollte es eigentlich gehen, aber Leute nur auf Basis des voxforge Audio Materials etwas entwickeln sollte man Fremdwörter in den Submissions möglichst gering halten.

Re: Updated 12k Word 16kHz Sphinx Model Available
User: guenter
Date: 4/14/2014 3:54 am
Views: 74
Rating: 0

Updated model is available now at

http://goofy.zamia.org/voxforge/de/

the model covers all german voxforge submissions as of yesterday (except the openpento submissions which will require a more sophisticated noise model). dictionary is up to 15423 words now.

Statistics:

total     34930 files, total    length:  2791.65min
reviewed  34930 files, reviewed length:  2791.65min (100% done)
good      32856 files, good     length:  2624.69min ( 94% good)

unique words in all submissions: 14951, unique words in reviewed good submissions: 14848

Data per user: 

ALI                       :     0.83min    67 words
AdrianTovar               :     5.70min   445 words   0.0% ts werr
BRwgt                     :     8.43min   693 words   0.0% ts werr
Black_Galaxy              :     0.69min    69 words   0.0% ts werr
Crazo                     :     2.20min   203 words   6.5% ts werr
DanielNeuhaus             :     3.43min   372 words  14.6% ts werr
Defense                   :     1.48min   127 words   0.0% ts werr
DirkSchnelleWalka         :     1.41min   142 words   0.0% ts werr
FrankJger                 :     0.96min    63 words
HeavensRevenge            :    28.97min  2755 words   1.0% ts werr
Hornochse                 :     2.23min   281 words   0.0% ts werr
J_N                       :     4.11min   379 words  14.8% ts werr
Komeran                   :     1.62min   149 words   0.0% ts werr
LinuxFan                  :     0.66min    68 words   0.0% ts werr
LucasK                    :     3.27min   311 words   0.0% ts werr
M11                       :     3.19min   294 words 100.0% ts werr
M12                       :     2.93min   267 words
M20                       :     4.81min   430 words   0.0% ts werr
M28                       :     4.87min   413 words
M32                       :     6.08min   537 words
M35                       :     7.29min   560 words 100.0% ts werr
MackyMesser               :     2.68min   222 words   0.0% ts werr
Manu                      :   221.94min 19842 words   0.6% ts werr
Me                        :     0.92min    69 words   0.0% ts werr
MingTran                  :     0.00min     7 words
Nevs                      :     0.16min    12 words
OssiDlz                   :     0.85min    79 words   0.0% ts werr
RBwgt                     :     0.84min    63 words   0.0% ts werr
RainCT                    :     0.43min    37 words
Rebbidebbi                :     2.93min   279 words   0.0% ts werr
Spacefish                 :     1.55min   156 words   0.0% ts werr
Steltek                   :     1.72min   231 words   0.0% ts werr
Styx85                    :     0.90min    86 words
Susi                      :     0.93min    59 words   0.0% ts werr
Tazy                      :     0.09min     8 words
TheLinuxist               :     1.68min   150 words   0.0% ts werr
Thomas                    :     4.90min   415 words   0.0% ts werr
UrbanCMC                  :     2.71min   215 words   0.0% ts werr
alexander                 :     0.71min    72 words   0.0% ts werr
andromeda                 :     0.97min    72 words
anonymous                 :    71.12min  6018 words   4.4% ts werr
b166er                    :     0.23min    22 words
cairn                     :    19.39min  1569 words   4.7% ts werr
cib                       :     0.06min    10 words
computing                 :    11.01min  1269 words   3.2% ts werr
doogent                   :     0.80min    73 words
dturing                   :     1.91min   212 words   0.0% ts werr
freuerin                  :     1.33min   146 words   0.0% ts werr
geh_weida                 :     0.07min     8 words
geon                      :     7.21min   743 words   1.0% ts werr
gero                      :     0.71min    64 words  33.3% ts werr
gouppe                    :     2.66min   127 words  20.0% ts werr
grisch                    :     0.86min    71 words   0.0% ts werr
guenter                   :   600.73min 61527 words   0.7% ts werr
ich                       :     4.18min   335 words   0.0% ts werr
jcp                       :     1.87min   131 words   0.0% ts werr
justmoon                  :     1.40min   162 words   0.0% ts werr
laserman                  :     2.88min   216 words   0.0% ts werr
lasser                    :    22.35min  2166 words   1.0% ts werr
locoloco                  :     1.65min   155 words   0.0% ts werr
m0rbid                    :     0.21min    24 words  18.2% ts werr
marv                      :     5.26min   432 words   2.3% ts werr
mjw                       :     4.32min   433 words   2.2% ts werr
mk                        :     0.97min    76 words
mr123                     :     0.79min    52 words
mweinelt                  :     1.26min   170 words  15.4% ts werr
pszacherski               :     8.65min   903 words   0.0% ts werr
ralfherzog                :  1408.82min 94211 words   0.8% ts werr
rebecca                   :     7.33min   580 words  12.0% ts werr
rmmg                      :    43.02min  3454 words   1.7% ts werr
robin                     :     0.04min     4 words
rwthafu                   :     4.89min   498 words   0.0% ts werr
sagef                     :     2.91min   204 words   3.2% ts werr
schiebi                   :     0.09min     8 words
sgottwald                 :     0.80min    77 words   0.0% ts werr
stephsphynx               :     0.07min     9 words
steviehs                  :     1.91min   141 words   0.0% ts werr
suther                    :     0.88min    64 words   0.0% ts werr
thhoof                    :    14.09min  1069 words   0.0% ts werr
thisss                    :     1.87min   151 words   0.0% ts werr
timiobaumann              :     0.72min    77 words   0.0% ts werr
timobaumann               :    14.95min  1532 words   7.4% ts werr
tolleiv                   :     5.22min   584 words   1.4% ts werr
wmwie                     :     1.13min    89 words   0.0% ts werr

Total: test set has 14899 words 176 errors =>   1.2%

 

Re: Updated 12k Word 16kHz Sphinx Model Available
User: Manu
Date: 4/14/2014 6:12 am
Views: 206
Rating: 0

Thank you very much guenter for the work and so much effort:-)


I made a base model for simon from this model and attached it here.


This is also linked from KDE-Files.org


Thanks again.


EDIT: New version :-)

voxforge-de-r20140416.sbm voxforge-de-r20140416.sbm
Re: Updated 12k Word 16kHz Sphinx Model Available
User: mifritscher
Date: 4/21/2014 10:23 am
Views: 386
Rating: 0

Thanks for your effort! Tiny problem: the demonstration script in your archive refers to model_parameters/voxforge.cd_cont_4000, but the directory is called model_parameters/voxforge.cd_cont_3000 . A question: Can I use your files with g2p ( https://code.google.com/p/phonetisaurus/ ) somehow? The main problem is that I want to create my own dictionary, but g2p has only training data for the english language. Your already provide a .dic-File, but I want to make my own with only the words I need, additionally I have have some special (key-)words with aren't in your dictionary, and I don't want to transcribe them manually ;-) Examples are Cubie, Nibobee and Julya

Re: Updated 12k Word 16kHz Sphinx Model Available
User: nsh
Date: 4/27/2014 2:14 pm
Views: 233
Rating: 0

> Can I use your files with g2p ( https://code.google.com/p/phonetisaurus/ ) somehow?

Yes, you can use the dictionary in phonetisaurus. You could probably just try it. You might want to convert the format though (care about number of spaces between word and phonemes).

 

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