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LeMUR browser support
LeMUR can now be used from browsers, either via our JavaScript SDK or fetch
.
Check out the AssemblyAI changelog to see weekly accuracy and product improvements our team has been working on.
Powering incredible companies
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LeMUR can now be used from browsers, either via our JavaScript SDK or fetch
.
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Last week, we released Anthropic's Claude 3 model family into LeMUR, our LLM framework for speech.
You can now easily apply any of these models to your audio data. Learn more about how to get started in our docs or try out the new models in a no-code way through our playground.
For more information, check out our blog post about the release.
import assemblyai as aai
# Step 1: Transcribe an audio file
transcriber = aai.Transcriber()
transcript = transcriber.transcribe("./common_sports_injuries.mp3")
# Step 2: Define a prompt
prompt = "Provide a brief summary of the transcript."
# Step 3: Choose an LLM to use with LeMUR
result = transcript.lemur.task(
prompt,
final_model=aai.LemurModel.claude3_5_sonnet
)
print(result.response)
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We've fixed an issue which was causing the JavaScript SDK to surface the following error when using the SDK in the browser:
Access to fetch at 'https://api.assemblyai.com/v2/transcript' from origin 'https://exampleurl.com' has been blocked by CORS policy: Request header field assemblyai-agent is not allowed by Access-Control-Allow-Headers in preflight response.
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We've made significant improvements to the timestamp accuracy of our Speech-to-Text Best tier for English, Spanish, and German. 96% of timestamps are accurate within 200ms, and 86% of timestamps are now accurate within 100ms.
We've fixed a bug in which confidence scores of transcribed words for the Nano tier would sometimes be outside of the range [0, 1]
We've fixed a rare issue in which the speech for only one channel in a short dual channel file would be transcribed when disfluencies
was also enabled.
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We've made model improvements that significantly improve the accuracy of timestamps when using our Streaming Speech-to-Text service. Most timestamps are now accurate within 100 ms.
Our Streaming Speech-to-Text service will now return a new error 'Audio too small to be transcoded'
(code 4034
) when a client submits an audio chunk that is too small to be transcoded (less than 10 ms).