Speech to Text SDK

Convert audio to text with our easy-to-use SDKs. This guide will walk you through the essential steps to get started with speech transcription in your applications.

Prerequisites

Before you begin, make sure you have:

• An aiOla API key (get one here)
• Python 3.10+ (for Python SDK) or Node.js 18+ (for TypeScript SDK)

Step 1: Install the SDK

$
pip install aiola
>
# or for microphone support
>
pip install 'aiola[mic]'

Step 2: Set up authentication

First, you’ll need to generate an access token using your API key:

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from aiola import AiolaClient
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# Generate access token
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result = AiolaClient.grant_token(api_key='your-api-key')
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access_token = result.access_token
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# Create client
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client = AiolaClient(access_token=access_token)

Step 3: Transcribe an audio file

Here’s how to transcribe an audio file:

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# Transcribe audio file
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with open('path/to/your/audio.wav', 'rb') as audio_file:
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    transcript = client.stt.transcribe_file(
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        file=audio_file,
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        language='en'
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    )
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print(transcript)

Real-time streaming

For real-time audio streaming transcription, check out our dedicated Speech to Text Streaming Guide which covers:

• Live microphone streaming
• Event-based transcription handling
• Custom audio source streaming
• Keyword detection during streaming
• Connection management and error handling

Supported audio formats

The SDK supports the following audio formats:

• WAV (.wav)
• FLAC (.flac)
• AIFF (.aiff)
• M4A (.m4a)
• MP4 (.mp4)
• MOV (.mov)
• M4V (.m4v)
• AAC (.aac)
• MKV (.mkv)
• MP3 (.mp3)
• Opus (.opus)

File size limitations

• Maximum file size: 50 MB
• For larger files, consider using streaming transcription or splitting the audio into smaller chunks

Supported languages

The SDK supports the following languages:

• English (en)
• German (de)
• French (fr)
• Spanish (es)
• Portuguese (pr)
• Chinese (zh)
• Japanese (ja)
• Italian (it)

Error handling

Always implement proper error handling for your API calls:

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try:
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    with open('audio.wav', 'rb') as audio_file:
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        transcript = client.stt.transcribe_file(
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            file=audio_file,
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            language='en'
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        )
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    print(transcript)
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except Exception as e:
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    print(f"Transcription failed: {e}")

Advanced options

Keyword detection

You can enable keyword detection for more accurate transcription:

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# Keyword detection with custom transcription
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transcript = client.stt.transcribe_file(
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    file=audio_file,
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    language='en',
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    keywords={
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        "postgres": "PostgreSQL",
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        "k eight s": "Kubernetes"
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    }
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)

Custom configuration

For enterprise users, you can configure custom endpoints:

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# Custom base URL (enterprise)
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client = AiolaClient(
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    access_token=access_token,
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    base_url='https://your-custom-endpoint.com'
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)

Next steps

Now that you’ve successfully transcribed your first audio file, you can:

• Explore Real-time Streaming for live audio transcription
• Learn about Text to Speech SDK for converting text back to speech
• Check out the SDK repositories for more examples:
  • Python SDK
  • TypeScript SDK

Browser Examples

For web applications, check out our complete browser microphone streaming example:

• Browser Microphone Streaming - Full web app example showing real-time microphone transcription in the browser