Two tracks of writing. Voices from the contributor community on language, remote work, and life. Deep dives for developers building with speech and voice AI.
A working engineer's tour of speaker diarization: segmentation, embeddings, EEND, overlap, and how Diarization Error Rate behaves once you push it through a real pipeline.
You found the lead. Now you have to convert it. Here's the proposal structure I use, with the data on what actually closes, plus a fill-in template you can reuse.
A hands-on look at the augmentation techniques that make speech models more robust, which ones risk corrupting your transcripts, and a default recipe that holds up at scale.
Most freelancers price by gut feel and leave money on the table. Here's a cost-plus method to set a baseline rate, research your market, and raise it without losing clients.
Finding clients is the hardest part of freelancing. Here are nine concrete ways to land work in 2025, from LinkedIn to referrals to microtask platforms, with the numbers behind each one.
Word error rate is the default ASR accuracy metric, but the number means nothing without context. How WER is calculated, what counts as good, and what really moves it.

Co-founding Spirelight was a journey of testing partnerships and building a strong team. Discover how we aim to lead in AI training data across Europe.

Discover the best options for obtaining Danish voice training data for your AI models, from open-source datasets to custom collections. Learn how to create a targeted dataset that meets your specific needs.

In 2019, Andreas Kromann found himself in Southeast Asia, discovering the speech training data industry. This post explores the evolution of Spirelight and the key players who shaped its journey.