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Speech-To-Text

Inside the 2026 meeting assistant market map: Q&A with Naseem Moumene, Northzone

Meeting assistants are one of the most crowded AI categories right now. Granola, Fireflies, Fathom, Fyxer, Otter, Read — plus a long tail of vertical players, all competing for the same users.

Speech-To-Text

Custom vocabulary vs. custom spelling: which one to choose for better transcripts

Even the most advanced speech-to-text systems make mistakes when they hit brand names, technical acronyms, or non-standard pronunciations. For call centers and customer service platforms, these aren't minor glitches: they break workflows, misrepresent customer needs, and erode trust on both ends of the call.

Speech-To-Text

Build a customer interview library with Gladia, Airtable & Make.com

TL;DR: Most product teams lose qualitative insights to scattered audio and transcripts that misattribute quotes. A reliable interview library needs accurate async diarization, automated routing, and a searchable database. Gladia's Solaria-1 sets the accuracy floor (29% lower WER, 3x lower DER on conversational speech), and Make.com routes its structured JSON into Airtable automatically, turning raw recordings into a searchable, theme-tagged customer content library.

Ebook: Ultimate guide to using LLMs with speech recognition

Published on Jan 7, 2025
Ebook: Ultimate guide to using LLMs with speech recognition

Large Language Models (LLMs) have enabled businesses to build advanced AI-driven features, but navigating the many available models and optimization techniques isn't always easy.

If you’re looking to combine speech recognition (STT) and LLMs for cutting-edge voice apps, look no further! Our ultimate guide is finally here, and it’s filled with valuable strategies and hands-on insights from our work with hundreds of audio-first companies and extensive interviews with experts in AI note-taking, sales enablement and customer support.

What you'll learn:

  • The pros and cons of open-source vs proprietary models;
  • Best practices for optimizing LLM performance;
  • Key metrics and indicators to measure the success of STT systems;
  • A checklist for evaluating LLM and STT vendors for voice apps
  • ... and much more!
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