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Build confidently with
industry‑leading Speech AI models

Turn voice data into valuable insights and power cutting-edge products.

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>93%

Accuracy

99+

Available languages

12.5M

Hours of multilingual data

<600ms

Streaming latency

Speech-to-Text

Build on top of the most accurate Speech-to-Text model on the market with >93% accuracy.

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Features

Speaker Diarization

Multichannel

Automatic Language Detection

Filler Words

Profanity Filtering

Custom Spelling

Custom Vocabulary

And more

Streaming Speech-to-Text

Transcribe audio streams synchronously with high accuracy and low latency.

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Features

Auto Punctuation and Casing

Custom Vocabulary

End of Utterance Detection

ITN/Formatting

Speech Understanding

Extract maximum value from voice data with Audio Intelligence, and leverage Large Language Models with LeMUR.

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Audio Intelligence Models

Entity Detection

PII Redaction

Topic Detection

Sentiment Analysis

Key Phrases

And more

LeMUR: LLMs for speech

Call Transcript (04.02.2024)

Thank you for calling Acme Corporation, Sarah speaking. How may I assist you today? Hi Sarah, this is John. I’m having trouble with my Acme Widget. It seems to be malfunctioning. I’m sorry to hear that, John. Let’s get that sorted out for you. Could you please provide me with the serial number of your widget? Thank you, John. Now, could you describe the issue you’re experiencing with your widget? Well, it’s not turning on at all, even though I’ve replaced the batteries.

The customer, John, called Acme Corporation's customer service department to report a malfunction with his widget. Sarah, the representative, attempted troubleshooting but concluded that the widget needed repair under warranty. She offered to send a prepaid shipping label for the return of the widget.
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import assemblyai as aai

transcriber = aai.Transcriber()
transcript = transcriber.transcribe(URL, config)

print(transcript)
{
  "id": "6rlr37h8f4-e310-4e23-bbf3-ea5f347dc684",
  "language_code": "en_us",
  "status": "completed",
  "text": "Runner's knee is a condition characterized by pain behind or around the kneecap...",
  "confidence": 0.98122,
  "audio_duration": 3200,
  "words": [
    { "text": "Runner's", "start": 0, "end": 550, "speaker": "A", "confidence": 0.98113 },
    { "text": "knee", "start": 580, "end": 1130, "speaker": "A", "confidence": 0.95417 }
  ]
}