Re: [Kaldi-users] Integration of Kaldi into a voice-to-voice translator

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When I will finish the Python wrapper and writing the docs, I will publish
it probably on www.bitbucket.org like a git repository.
I can drop a link somewhere if anybody would be interested.

Ondra

On 14 May 2013 18:26, Ondrej Platek <ond...@gm...> wrote:

> Good to hear. I am trying from last week to learn how was it designed.
> When are you going to commit the changes? In days in weeks?
> I would like to use the new code to build upon.
>
> I would like to run some experiments first,
> than I need to build a python wrapper (my project requirements).
> Currently I am finishing a python wrapper for the compute-mfcc-featscc ,
> gmm-latgen-faster.cc and lattice-best-path.cc
> using https://cffi.readthedocs.org/en/release-0.6/.
>
> Basically I am trying to build shared library containing
> functionality of the  compute-mfcc-featscc , gmm-latgen-faster.cc and
> lattice-best-path.cc.
> Than the rest is very easy using python-cffi (
> https://cffi.readthedocs.org/en/release-0.6/).
> I guess there is no plan to distribute Kaldi as shared library, right?
> (Pity for me)
>
> Ondra
>
>
> On 14 May 2013 18:13, Mailing list used for User Communication and Updates
> <kal...@li...> wrote:
>
>> By the way, since we are talking about the online decoder, I should
>> mention that I am just about to commit some changes, involving a
>> reorganization of the internal code and the addition of unit-tests.  Vassil
>> has checked that it still works for his demo.
>>
>> Dan
>>
>>
>>
>> On Tue, May 14, 2013 at 12:09 PM, Daniel Povey <dp...@gm...> wrote:
>>
>>> You have to be careful that you give the online decoder the right
>>> options corresponding tot the features that you used.  See if there are any
>>> non-default options in your MFCC extraction or PLP extraction, for
>>> instance, and that the LDA window is set correctly.
>>>
>>> Dan
>>>
>>>
>>>
>>> On Tue, May 14, 2013 at 10:10 AM, Mailing list used for User
>>> Communication and Updates <kal...@li...> wrote:
>>>
>>>> As I said on my data have results like 70% WER. It is due to some bug,
>>>> which I have not fixed yet.
>>>>
>>>> In the online demo I tried to use our test (quite general data - in
>>>> terms of LM) and test it against online demo,
>>>> because as far as I understood it the online demo was trained on the
>>>> same data which are in supplied as the test data.
>>>>
>>>> Basically, I was asking for the numbers because I need to know if I
>>>> have still bug in my script or it is just normal performance.
>>>>
>>>> Thansk
>>>>
>>>> Ondra
>>>>
>>>>
>>>>
>>>>
>>>> On 14 May 2013 15:39, Mailing list used for User Communication and
>>>> Updates <kal...@li...> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I don't have specific numbers to share (as I said the online decoder
>>>>> is not rigorously tested as far as I know). In principle I think the
>>>>> online decoder should perform slightly worse than the offline versions
>>>>> due to things like online CMN computation.
>>>>>
>>>>> What do you mean exactly when you say that the results for the online
>>>>> demo are not so good? As far as I remember the WER for the test WAV
>>>>> files was about 7%, which is not so bad as today's speech recognition
>>>>> goes. Of course the WER in this case is so low, because the language
>>>>> model is relatively small and perfectly matches the test files (the LM
>>>>> is trained on the text corresponding to the audio book from which the
>>>>> test utterances were taken - not the best practice of course).
>>>>>
>>>>> Vassil
>>>>>
>>>>> On Tue, May 14, 2013 at 2:59 PM, Mailing list used for User
>>>>> Communication and Updates <kal...@li...> wrote:
>>>>> > Hi Vassil,
>>>>> >
>>>>> > May I asked about the performance (in terms of WER/SER) of online
>>>>> decoder?
>>>>> >
>>>>> > What is the expected WER for online-wav-gmm-decode-faster,
>>>>> > if I reached with  gmm-latgen-faster scores in table below?
>>>>> > I would like to use the same trained models for
>>>>> online-wav-gmm-decode-faster
>>>>> > as
>>>>> > I used for  gmm-latgen-faster (and lattice-best-path).
>>>>> >
>>>>> > exp             RT coef         WER
>>>>> > _ri3b_fmmi_b    11.33336625     19.42
>>>>> > tri2b_mpe       1.2307175       21.22
>>>>> > mono            2.8952          49.88
>>>>> > tri3b_mmi       1.24198625      20.01
>>>>> > tri1            2.398165        28.13
>>>>> > tri2b_mmi       1.65662125      20.34
>>>>> > tri2a           2.15838         28.43
>>>>> > tri2b           1.451105        27.96
>>>>> > tri3b           1.0596075       27.79
>>>>> > tri3b_fmmi_c    11.4361875      19.13
>>>>> > tri2b_mmi_b0.05 2.0089575       19.64
>>>>> > tri3b_fmmi_d    16.1227625      19.5
>>>>> >
>>>>> > The names and the core settings of experiments are the same as in
>>>>> > egs/voxforge/s5/run.sh
>>>>> >
>>>>> >
>>>>> > With the online-wav-gmm-decode-faster
>>>>> > I reached really bad scores due to bugs (which I still need to fix),
>>>>> > but still also in the online demo the results are not so nice.
>>>>> >
>>>>> > Thanks for any help
>>>>> >
>>>>> > Ondra Platek
>>>>> >
>>>>> >
>>>>> > On 26 April 2013 15:35, Mailing list used for User Communication and
>>>>> Updates
>>>>> > <kal...@li...> wrote:
>>>>> >>
>>>>> >> Hi,
>>>>> >> as for taking input from a microphone you might want to have a look
>>>>> at
>>>>> >> the (optional) online decoder. There is a simple demo script in
>>>>> >> egs/voxforge/online-demo. There is also a version that can decode
>>>>> .wav
>>>>> >> files without a separate feature extraction step. The code is not
>>>>> >> extensively tested and lacks some polish and flexibility, but
>>>>> perhaps
>>>>> >> you can use it as an example.
>>>>> >>
>>>>> >> Vassil
>>>>> >>
>>>>> >> On Fri, Apr 26, 2013 at 3:55 PM, Mailing list used for User
>>>>> >> Communication and Updates <kal...@li...>
>>>>> wrote:
>>>>> >> > Dear all,
>>>>> >> > I'm working on the development of an R&D voice-to-voice module
>>>>> and I
>>>>> >> > would
>>>>> >> > like to use Kaldi for the transcription part (we made some tests
>>>>> with
>>>>> >> > PocketSphinx but we found that Kaldi is more adapted for our
>>>>> task).
>>>>> >> >
>>>>> >> > The problem is that I'm not really expert in speech2text (Kaldi
>>>>> models
>>>>> >> > will
>>>>> >> > be provided by another team) and I did not found scripts (or
>>>>> plugins)
>>>>> >> > allowing an easy integration of Kaldi : How to manage streams
>>>>> (with
>>>>> >> > gstreammer for example)? how we can decode a single wav file? etc.
>>>>> >> >
>>>>> >> > Is someone else has already handle these problems? are there any
>>>>> scripts
>>>>> >> > to
>>>>> >> > facilitate this task?
>>>>> >> >
>>>>> >> > thanks in advance for your reply,
>>>>> >> >
>>>>> >> > Best regards
>>>>> >> >
>>>>> >> >
>>>>> >> >
>>>>> >> >
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>>>>> >> >
>>>>> >>
>>>>> >>
>>>>> >>
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