Transcribe a pre-recorded audio file

Overview

By the end of this tutorial, you’ll be able to:

• Transcribe a pre-recorded audio file.
• Enable Speaker Diarization to detect speakers in an audio file.

Here’s the full sample code for what you’ll build in this tutorial:

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import assemblyai as aai
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aai.settings.api_key = "<YOUR_API_KEY>"
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transcriber = aai.Transcriber()
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# You can use a local filepath:
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# audio_file = "./example.mp3"
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# Or use a publicly-accessible URL:
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audio_file = (
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    "https://assembly.ai/sports_injuries.mp3"
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)
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config = aai.TranscriptionConfig(speaker_labels=True)
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transcript = transcriber.transcribe(audio_file, config)
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if transcript.status == aai.TranscriptStatus.error:
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    print(f"Transcription failed: {transcript.error}")
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    exit(1)
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print(transcript.text)
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for utterance in transcript.utterances:
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	print(f"Speaker {utterance.speaker}: {utterance.text}")

Before you begin

To complete this tutorial, you need:

• Python, TypeScript, Go, Java, .NET, or Ruby installed.
• A free AssemblyAI account.

Step 1: Install the SDK

$
pip install assemblyai

Step 2: Configure the SDK

In this step, you ‘ll create an SDK client and configure it to use your API key.

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import assemblyai as aai
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aai.settings.api_key = "<YOUR_API_KEY>"
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transcriber = aai.Transcriber()

Step 3: Submit audio for transcription

In this step, you’ll submit the audio file for transcription and wait until it’s completes. The time it takes to process an audio file depends on its duration and the enabled models. Most transcriptions complete within 45 seconds.

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audio_file = "https://assembly.ai/sports_injuries.mp3"

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audio_file = "./example.mp3"

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transcript = transcriber.transcribe(audio_file)

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if transcript.error:
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   print(transcript.error)
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   exit(1)

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print(transcript.text)

You’ve successfully transcribed your first audio file. You can see all submitted transcription jobs in the Processing queue.

Step 4: Enable additional AI models

You can extract even more insights from the audio by enabling any of our AI models using transcription options. In this step, you’ll enable the Speaker diarization model to detect who said what.

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config = aai.TranscriptionConfig(speaker_labels=True)
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transcript = transcriber.transcribe(audio_file, config)

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for utterance in transcript.utterances:
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	print(f"Speaker {utterance.speaker}: {utterance.text}")

Many of the properties in the transcript object only become available after you enable the corresponding model. For more information, see the models under Speech-to-Text and Audio Intelligence.

Next steps

In this tutorial, you’ve learned how to generate a transcript for an audio file and how to extract speaker information by enabling the Speaker diarization model.

Want to learn more?

• For more ways to analyze your audio data, explore our Audio Intelligence models.
• If you want to transcribe audio in real-time, see Transcribe streaming audio from a microphone.
• To search, summarize, and ask questions on your transcripts with LLMs, see LeMUR.

Need some help?

If you get stuck, or have any other questions, we’d love to help you out. Contact our support team at support@assemblyai.com or create a support ticket.