Blog
Speech-To-Text
The evolution and impact of Speech AI: An in-depth conversation with Gladia's CEO Jean-Louis
Once in a while, we like to zoom out of our day-to-day to reflect on the bigger trends affecting our customers to, ultimately, adapt our product accordingly. Today, what are the key shifts happening in voice-first platforms, and how can speech recognition help them to navigate these?
Speech-To-Text
AI Model Biases: What went wrong with Whisper by OpenAI?
When you start working with an AI model, however powerful, you can never be 100% sure of what will happen with it in practice. We've worked with Whisper ASR by OpenAI since its release in 2022 – and what we discovered is nothing short of surprising.
Speech-To-Text
Enhancing CX with AI: Key trends to watch 2024
AI is transforming contact centers at an accelerating pace. Speech AI technologies are at the forefront of this revolution, enabling companies to provide better customer experiences through a combination of advanced agent-assist techniques and fully automated interactions that feel natural and human-like.
Case Studies
How VEED is streamlining video editing and subtitles with AI transcription
User-generated content has become a cornerstone of the internet-driven economy. As part of this shift, various platforms have emerged to provide easy-to-use tools to create high-quality video content in a matter of minutes — with AI transcription playing a foundational role in their product development.
Tutorials
How to build a speaker identification system for recorded online meetings
Virtual meeting recordings are becoming increasingly used as a source of valuable business knowledge. However, given the large amount of audio data produced in meetings by companies, getting the full value out of recorded meetings can be tricky.
Speech-To-Text
Should you trust WER?
Word Error Rate (WER) is a metric that evaluates the performance of ASR systems by analyzing the accuracy of speech-to-text results. WER metric allows developers, scientists, and researchers to assess ASR performance. A lower WER indicates better ASR performance, and vice versa. The assessment allows for optimizing the ASR technologies over time and helps to compare speech-to-text models and providers for commercial use.