Build confidently with
industry‑leading Speech AI models
Turn voice data into valuable insights and power cutting-edge products.
>92.5%
99+
12.5M
<600ms
Speech-to-Text
Build on top of the most accurate Speech-to-Text model on the market with >92.5% accuracy.
Learn moreFeatures
Speaker Diarization
Dual Channel
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.
Learn moreFeatures
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.
Learn moreAudio 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.
Get started in seconds
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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 }
]
}