Deepgram

Numbers, dates, and acronyms break text-to-speech in specific, documented ways. Here's where normalization lives — and why it depends on your model.

Using multiple transcription engines and an LLM judge to catch errors in voice-to-text — especially tricky technical terms.

How to build professional phone systems with Twilio — IVRs, round-robin routing, voicemail transcription, and SIP setup.

From try-except blocks to planning agents that route around failures intelligently.

getUserMedia returns audio, but not raw audio. Here's what browsers actually do to your mic feed before it hits your server.

Base64 isn’t compression — it’s a safe transport encoding. Here’s how it works with audio APIs and where its limits are.

Cleaning audio before transcription can increase errors by up to 46%. Here's the right approach for your voice app.

How voice activity detection shapes every step of the voice tech pipeline, and why it’s harder than it seems.

Stop guessing. We break down the critical trade-offs between model size, latency, and sample rate for production-ready voice apps.

Raw APIs handle models, but who manages the audio plumbing? We break down Vapi, LiveKit, and Pipecat.

Explore the engineering battle to bring low-latency AI voice input to Linux while navigating the strict security of Wayland and GNOME 50.

Why does voice typing feel so clunky compared to recording a memo? We explore the technical hurdles of real-time AI transcription.

Herman and Corn break down the difference between speaker diarization and identification to help automate meeting transcripts.