Fixing Timestamp Drift in ASR: A New Approach
Autoregressive ASR systems face a challenge with timestamp drift during long non-speech segments. The proposed REDDIT framework tackles this, boosting alignment without losing other ASR capabilities.
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Drax: A Discrete Flow Matching Framework for State-of-the-Art Speech Recognition
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Beyond Autoregression: LLaDA2.1 and the Case for Self-Editing Language Models
Introduction Every mainstream large language model today generates text the same way: one token at a time, left to right, no looking back. I
CraneAI Labs Releases v1.2 of Streaming ASR Model for Luganda, Shona, and Swahili
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Challenges with Open-Source Text-to-Speech Technology for Podcast Generation
or at least the open versions of it. I have this very stupid rule. A couple of years ago I decided to turn this blog into a podcast. At the
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How Together AI built the world’s fastest speech-to-text stack
Together AI built the fastest speech-to-text stack on Artificial Analysis by treating ASR as a full-path systems problem, not just a GPU inf
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