Introducing LeMUR
LeMUR is the easiest way to build LLM apps on spoken data - search, summarize, and ask questions, with knowledge of your spoken data.
Launch
Conformer-2: a state-of-the-art speech recognition model trained on 1.1M hours of data
We're introducing Conformer-2, our latest AI model for automatic speech recognition. Conformer-2 is trained on 1.1M hours of English audio data, extending Conformer-1 to provide improvements on proper nouns, alphanumerics, and robustness to noise.
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.
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.
