Product improvements

Last week, we released Anthropic's Claude 3 model family into LeMUR, our LLM framework for speech.

• Claude 3.5 Sonnet
• Claude 3 Opus
• Claude 3 Sonnet
• Claude 3 Haiku

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)

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.

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.

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).

We've deployed changes which now permit variable-bitrate video files to be submitted to our API.

We've fixed a recent bug in which audio files with a large amount of silence at the beginning of the file would fail to transcribe.