mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-08 09:32:20 +00:00
66 lines
2.6 KiB
ReStructuredText
66 lines
2.6 KiB
ReStructuredText
Huggingface spaces
|
|
==================
|
|
|
|
We have integrated the server framework
|
|
`sherpa <http://github.com/k2-fsa/sherpa>`_
|
|
with `Huggingface spaces <https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_
|
|
so that you can try pre-trained models from within your browser
|
|
without the need to download or install anything.
|
|
|
|
All you need is a browser, which can be run on Windows, macOS, Linux, or even on your
|
|
iPad and your phone.
|
|
|
|
Start your browser and visit the following address:
|
|
|
|
`<https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_
|
|
|
|
and you will see a page like the following screenshot:
|
|
|
|
.. image:: ./pic/hugging-face-sherpa.png
|
|
:alt: screenshot of `<https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_
|
|
:target: https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition
|
|
|
|
You can:
|
|
|
|
1. Select a language for recognition. Currently, we provide pre-trained models
|
|
from ``icefall`` for the following languages: ``Chinese``, ``English``, and
|
|
``Chinese+English``.
|
|
2. After selecting the target language, you can select a pre-trained model
|
|
corresponding to the language.
|
|
3. Select the decoding method. Currently, it provides ``greedy search``
|
|
and ``modified_beam_search``.
|
|
4. If you selected ``modified_beam_search``, you can choose the number of
|
|
active paths during the search.
|
|
5. Either upload a file or record your speech for recognition.
|
|
6. Click the button ``Submit for recognition``.
|
|
7. Wait for a moment and you will get the recognition results.
|
|
|
|
The following screenshot shows an example when selecting ``Chinese+English``:
|
|
|
|
.. image:: ./pic/hugging-face-sherpa-3.png
|
|
:alt: screenshot of `<https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_
|
|
:target: https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition
|
|
|
|
|
|
In the bottom part of the page, you can find a table of examples. You can click
|
|
one of them and then click ``Submit for recognition``.
|
|
|
|
.. image:: ./pic/hugging-face-sherpa-2.png
|
|
:alt: screenshot of `<https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_
|
|
:target: https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition
|
|
|
|
YouTube Video
|
|
-------------
|
|
|
|
We provide the following YouTube video demonstrating how to use
|
|
`<https://huggingface.co/spaces/k2-fsa/automatic-speech-recognition>`_.
|
|
|
|
.. note::
|
|
|
|
To get the latest news of `next-gen Kaldi <https://github.com/k2-fsa>`_, please subscribe
|
|
the following YouTube channel by `Nadira Povey <https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw>`_:
|
|
|
|
`<https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw>`_
|
|
|
|
.. youtube:: ElN3r9dkKE4
|