Product improvements

We've improved our timestamp algorithm, yielding higher accuracy for long numerical strings like credit card numbers, phone numbers, etc.

We've released a fix for no-space languages like Japanese and Chinese. While transcripts for these languages correctly contain no spaces in responses from our API, the text attribute of the utterances key previously contained spaces. These extraneous spaces have been removed.

We've improved Universal-2's formatting for punctuation, lowering the likelihood of consecutive punctuation characters such as ?'.

We now offer multichannel transcription, allowing users to transcribe files with up to 32 separate audio channels, making speaker identification easier in situations like virtual meetings.

You can enable multichannel transcription via the `multichannel` parameter when making API requests. Here's how you can do it with our Python SDK:

import assemblyai as aai

aai.settings.api_key = "YOUR_API_KEY" 
audio_file = "path/to/your/file.mp3"

config = aai.TranscriptionConfig(multichannel=True)

transcriber = aai.Transcriber(config=config)
transcript = transcriber.transcribe(audio_url)

print(transcript.json_response["audio_channels"])
print(transcript.utterances)

You can learn more about multichannel transcription in our Docs.

Last week we released Universal-2, our latest Speech-to-Text model. Universal-2 builds upon our previous model Universal-1 to make significant improvements in "last mile" challenges critical to real-world use cases - proper nouns, formatting, and alphanumerics.

Comparison of error rates for Universal-2 vs Universal-1 across overall performance (Standard ASR) and four last-mile areas, each measured by the appropriate metric

Universal-2 is now the default model for English files sent to our `v2/transcript` endpoint for async processing. You can read more about Universal-2 in our announcement blog or research blog, or you can try it out now on our Playground.

The following models were removed from LeMUR: anthropic/claude-instant-1-2 and basic (legacy, equivalent to anthropic/claude-instant-1-2), which will now return a 400 validation error if called.

These models were removed due to Anthropic sunsetting legacy models in favor of newer models which are more performant, faster, and cheaper. We recommend users who were using the removed models switch to Claude 3 Haiku (anthropic/claude-3-haiku).

We recently observed a degradation in accuracy when transcribing French files through our API. We have since pushed a bugfix to restore performance to prior levels.

We've improved error messaging for greater clarity for both our file download service and Invalid LLM response errors from LeMUR.

We've released a fix to ensure that rate limit headers are always returned from LeMUR requests, and not just 200 and 400 responses.