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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We’ve fixed an issue in which the last character in an alphanumeric sequence could fail to be transcribed. The fix is effective immediately and constitutes a 95% reduction in errors of this type.
We’ve fixed an issue in which consecutive identical numbers in a long number sequence could fail to be transcribed. This fix is effective immediately and constitutes a 66% reduction in errors of this type.
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We’ve made improvements to the Speaker Labels model, adjusting the impact of the speakers_expected parameter to better allow the model to determine the correct number of unique speakers, especially in cases where one or more speakers talks substantially less than others.
We’ve expanded our caching system to include additional third-party resources to help further ensure our continued operations in the event of external resources being down.
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We’ve made significant improvements to our transcoding pipeline, resulting in a 98% overall speedup in transcoding time and a 12% overall improvement in processing time for our asynchronous API.
We’ve implemented a caching system for some third-party resources to ensure our continued operations in the event of external resources being down.
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We’re introducing our new framework LeMUR, which makes it simple to apply Large Language Models (LLMs) to transcripts of audio files up to 10 hours in length.
LLMs unlock a range of impressive capabilities that allow teams to build powerful Generative AI features. However, building these features is difficult due to the limited context windows of modern LLMs, among other challenges that necessitate the development of complicated processing pipelines.
LeMUR circumvents this problem by making it easy to apply LLMs to transcribed speech, meaning that product teams can focus on building differentiating Generative AI features rather than focusing on building infrastructure. Learn more about what LeMUR can do and how it works in our announcement blog, or jump straight to trying LeMUR in our Playground.
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We’ve upgraded to a new and more accurate PII Redaction model, which improves credit card detections in particular.
We’ve made stability improvements regarding the handling and caching of web requests. These improvements additionally fix a rare issue with punctuation detection.