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Synchronous speech recognition using the Python SDK

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Updated at March 28, 2025

Below, we provide an example of synchronous speech recognition from an audio file using the SpeechKit Python SDK. This example uses the following parameters:

To use the Python SDK, the yandex-speechkit package is required.

Authentication is performed under a service account using an API key or IAM token. Learn more about authentication in the SpeechKit API.

Getting started

  1. Create a service account and assign the ai.speechkit-stt.user role to it.
  2. Get an API key for the service account and save it.
  3. Download a sample audio file for recognition or generate your own one.

Create an application for synchronous speech recognition

  1. Install the yandex-speechkit package using the pip package manager:

    pip install yandex-speechkit

    The installation was tested on Python 3.9. For the minimum allowed Python version, see the SDK website.

    If a grpcio-tools package version conflict occurs, see Resolving version conflicts during the installation of Python SDK.

  2. Create a file named test.py and add the following code to it:

    from argparse import ArgumentParser
from speechkit import model_repository, configure_credentials, creds
from speechkit.stt import AudioProcessingType

# Authentication with an API key.
configure_credentials(
   yandex_credentials=creds.YandexCredentials(
      api_key='<API_key>'
   )
)

def recognize(audio):
   model = model_repository.recognition_model()

   # Specify the recognition settings.
   model.model = 'general'
   model.language = 'ru-RU'
   model.audio_processing_type = AudioProcessingType.Full

   # Recognizing speech in the specified audio file and outputting the results to the console.
   result = model.transcribe_file(audio)
   for c, res in enumerate(result):
      print('=' * 80)
      print(f'channel: {c}\n\nraw_text:\n{res.raw_text}\n\nnorm_text:\n{res.normalized_text}\n')
      if res.has_utterances():
         print('utterances:')
         for utterance in res.utterances:
            print(utterance)

if __name__ == '__main__':
   parser = ArgumentParser()
   parser.add_argument('--audio', type=str, help='audio path', required=True)

   args = parser.parse_args()

   recognize(args.audio)

    Where:

    • api_key: Service account API key.

    • audio: Audio recording file path.

    • model: Recognition model.

    • language: Recognition language.

    • audio_processing_type: Audio processing method.

      The Python SDK does not support streaming and asynchronous recognition, but you can simulate these features. To do this, set the following value in the test.py file, the audio_processing_type parameter:

      • AudioProcessingType.Stream for streaming recognition.
      • AudioProcessingType.Full for asynchronous recognition.

  3. Run the created file:

    python3 test.py --audio speech.pcm

    Where --audio is the path to the audio file for recognition.

    The result contains recognized speech:

    channel: 0

raw_text:
i'm yandex speechkit i can turn any text into speech now you can too

norm_text:
I'm Yandex SpeechKit, I can turn any text into speech, now you can too.

utterances:
- I'm Yandex SpeechKit, I can turn any text into speech, now you can too. [0.419, 6.379]

See also

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Authentication in the Python SDK
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Speech synthesis using the Python SDK