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Cover image for AI System Makes Speech Recognition Text 3x Cleaner and Faster Using Unified Neural Network
Mike Young
Mike Young

Posted on • Originally published at aimodels.fyi

AI System Makes Speech Recognition Text 3x Cleaner and Faster Using Unified Neural Network

This is a Plain English Papers summary of a research paper called AI System Makes Speech Recognition Text 3x Cleaner and Faster Using Unified Neural Network. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

  • New system for formatting raw ASR text output with punctuation and proper capitalization
  • Combines three key tasks: punctuation restoration, truecasing, and text normalization
  • Uses a unified neural network approach rather than separate models
  • Achieves state-of-the-art performance across multiple languages
  • Built to handle real-world ASR output challenges

Plain English Explanation

Speech recognition systems are great at turning spoken words into text, but the output often looks messy - no punctuation, wrong capitalization, and numbers written as words. This new system, called [Universal-2-TF](https://aimodels.fyi/papers/arxiv/universal-2-tf-robust-all-ne...

Click here to read the full summary of this paper

Image of AssemblyAI tool

Transforming Interviews into Publishable Stories with AssemblyAI

Insightview is a modern web application that streamlines the interview workflow for journalists. By leveraging AssemblyAI's LeMUR and Universal-2 technology, it transforms raw interview recordings into structured, actionable content, dramatically reducing the time from recording to publication.

Key Features:
🎥 Audio/video file upload with real-time preview
🗣️ Advanced transcription with speaker identification
⭐ Automatic highlight extraction of key moments
✍️ AI-powered article draft generation
📤 Export interview's subtitles in VTT format

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