> ## Documentation Index
> Fetch the complete documentation index at: https://assemblyai.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Migration guide: Google Speech-to-Text to AssemblyAI

This guide walks through the process of migrating from Google Speech-to-Text (STT) to AssemblyAI for transcribing pre-recorded audio.

### Get Started

Before we begin, make sure you have an AssemblyAI account and an API key. You can [sign up](https://assemblyai.com/dashboard/signup) for a free account and get your API key from your dashboard.

## Side-by-side code comparison

Below is a side-by-side comparison of a basic snippet to transcribe a file by Google Speech-to-Text and AssemblyAI.

<Tabs groupId="language">
  <Tab language="google" title="Google STT">
    ```python expandable theme={null}
    from google.cloud import speech

    client = speech.SpeechClient()

    audio = speech.RecognitionAudio(
        uri="gs://cloud-samples-tests/speech/Google_Gnome.wav"
    )

    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=16000,
        language_code="en-US",
        model="video", # Chosen model
    )

    operation = client.long_running_recognize(config=config, audio=audio)

    print("Waiting for operation to complete...")
    response = operation.result(timeout=90)

    for i, result in enumerate(response.results):
        alternative = result.alternatives[0]
        print("-" * 20)
        print(f"First alternative of result {i}")
        print(f"Transcript: {alternative.transcript}")
    ```
  </Tab>

  <Tab language="aai" title="AssemblyAI">
    ```python expandable theme={null}
    import assemblyai as aai

    aai.settings.api_key = "YOUR-API-KEY"
    transcriber = aai.Transcriber()

    # You can use a local filepath:
    # audio_file = "./example.mp3"
    # Or use a publicly-accessible URL:
    audio_file = (
        "https://assembly.ai/sports_injuries.mp3"
    )

    config = aai.TranscriptionConfig(
        speech_models=["universal-3-5-pro", "universal-2"],
        language_detection=True,
    )
    transcript = transcriber.transcribe(audio_file, config)

    if transcript.status == aai.TranscriptStatus.error:
        print(f"Transcription failed: {transcript.error}")
        exit(1)

    print(transcript.text)
    ```
  </Tab>
</Tabs>

## Installation

<Tabs groupId="language">
  <Tab language="google" title="Google STT">
    ```python theme={null}
    from google.cloud import speech

    client = speech.SpeechClient()
    ```
  </Tab>

  <Tab language="aai" title="AssemblyAI">
    ```python theme={null}
    import assemblyai as aai

    aai.settings.api_key = "YOUR-API-KEY"
    transcriber = aai.Transcriber()
    ```
  </Tab>
</Tabs>

When migrating from Google Speech-to-Text to AssemblyAI, you'll first need to handle authentication and SDK setup:

Get your API key from your [AssemblyAI dashboard](https://www.assemblyai.com/dashboard/home).
Things to know:

* Store your API key securely in an environment variable
* API key authentication works the same across all AssemblyAI SDKs

## Audio File Sources

<Tabs groupId="language">
  <Tab language="google" title="Google STT">
    ```python theme={null}
    audio = speech.RecognitionAudio(uri="gs://cloud-samples-tests/speech/Google_Gnome.wav")

    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=16000,
        language_code="en-US",
        model="video", # Chosen model
    )

    operation = client.long_running_recognize(config=config, audio=audio)
    ```
  </Tab>

  <Tab language="aai" title="AssemblyAI">
    ```python theme={null}
    transcriber = aai.Transcriber()

    # Local files
    transcript = transcriber.transcribe("./audio.mp3")

    # Public URLs
    transcript = transcriber.transcribe("https://example.com/audio.mp3")

    # S3 files (using pre-signed URLs)
    s3_client = boto3.client('s3')
    presigned_url = s3_client.generate_presigned_url(
        'get_object',
        Params={'Bucket': 'my-bucket', 'Key': 'audio.mp3'},
        ExpiresIn=3600
    )
    transcript = transcriber.transcribe(presigned_url)
    ```
  </Tab>
</Tabs>

Here are helpful things to know when migrating your audio input handling:

* There's no need to specify the audio encoding format when using AssemblyAI - we have a transcoding pipeline under the hood which works on all [supported file types](/faq/what-audio-and-video-file-types-are-supported-by-your-api) so that you can get the most accurate transcription.
* You can submit a local file, URL, stream, buffer, blob, etc., directly to our transcriber. Check out some common ways you can host audio files [here](/pre-recorded-audio/guides/transcribe_from_s3).
* You can transcribe audio files that are up to 10 hours long and you can transcribe multiple files in parallel. The default amount of jobs you can transcribe at once is 200 while on the PAYG plan.

## Basic Transcription

<Tabs groupId="language">
  <Tab language="google" title="Google STT">
    ```python theme={null}
    print("Waiting for operation to complete...")
    response = operation.result(timeout=90)

    for i, result in enumerate(response.results):
        alternative = result.alternatives[0]
        print("-" * 20)
        print(f"First alternative of result {i}")
        print(f"Transcript: {alternative.transcript}")
    ```
  </Tab>

  <Tab language="aai" title="AssemblyAI">
    ```python theme={null}
    transcriber = aai.Transcriber()

    config = aai.TranscriptionConfig(
        speech_models=["universal-3-5-pro", "universal-2"],
        language_detection=True,
    )
    transcript = transcriber.transcribe(audio_file, config)

    if transcript.status == aai.TranscriptStatus.error:
        print(f"Transcription failed: {transcript.error}")
    else:
        print(transcript.text)
    ```
  </Tab>
</Tabs>

Here are helpful things to know about our `transcribe` method:

* The SDK handles polling under the hood.
* The full transcript is directly accessible via `transcript.text`.
* English is the default language. We recommend specifying `speech_models=["universal-3-5-pro", "universal-2"]` for the highest accuracy.
* We have a [cookbook for error handling common errors](/pre-recorded-audio/guides/common_errors_and_solutions) when using our API.

## Adding Features

<Tabs groupId="language">
  <Tab language="google" title="Google STT">
    ```python theme={null}
    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=8000,
        language_code="en-US",
        enable_speaker_diarization=True,  # Speaker diarization
        diarization_speaker_count=2,  # Specify amount of speakers
        profanity_filter=True   # Remove profanity from transcript
    )
    ```
  </Tab>

  <Tab language="aai" title="AssemblyAI">
    ```python theme={null}
    config = aai.TranscriptionConfig(
        speech_models=["universal-3-5-pro", "universal-2"],
        language_detection=True,
        speaker_labels=True,  # Speaker diarization
        filter_profanity=True,  # Remove profanity from transcript
        speakers_expected=2,  # Specify amount of speakers in audio
    )

    transcript = transcriber.transcribe(audio_file, config)

    # Access speaker labels

    for utterance in transcript.utterances:
        print(f"Speaker {utterance.speaker}: {utterance.text}")
    ```
  </Tab>
</Tabs>

Key differences:

* Use `aai.TranscriptionConfig` to specify any extra features that you wish to use.
* The results for Speaker Diarization are stored in `transcript.utterances`. To see the full transcript response object, refer to our [API Reference](/api-reference).
* Check our [documentation](/speech-understanding/getting-started) for our full list of available features and their parameters.