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Introducing LeMUR, our new framework for applying powerful LLMs to transcribed speech

Launch

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Introducing LeMUR, our new framework for applying powerful LLMs to transcribed speech

LeMUR is our new framework for applying powerful LLMs to transcribed speech. With a single line of code, LeMUR can quickly process audio transcripts for up to 10 hours worth of audio content, which effectively translates into ~150k tokens, for tasks likes summarization and question answer.

Prachie Banthia's picture
Prachie Banthia
Conformer-1: A robust speech recognition model trained on 650K hours of data

Announcements

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Conformer-1: A robust speech recognition model trained on 650K hours of data

We’ve trained a Conformer speech recognition model on 650K hours of audio data. The new model, Conformer-1, approaches human-level performance for speech recognition, reaching a new state-of-the-art on real-world audio data.

Marco Ramponi's picture
Marco Ramponi

Developer Educator at AssemblyAI