A transcription pipeline is the chain of steps that turns live call audio into text and stored artefacts: branch the audio off the mix or individual speaker streams, segment it into utterances with voice activity detection, run automatic speech recognition, and then post-process into captions, searchable transcripts, summaries, and the recording itself. Doing it per-speaker rather than from a single mix gives accurate attribution of who said what, and good speech enhancement upstream lifts accuracy throughout. The pipeline is where audio leaves the real-time call and becomes durable data, raising design questions about latency (live captions versus after-the-fact transcripts), privacy and consent, storage, and where the recognition runs.
The book · Volume 5 of 7
Audio for Video: A Complete Guide to Sound in Video Products: From Jitter Buffers and Lip Sync to Atmos, Quality Metrics, and Neural Codecs
A transcription pipeline decides whether call audio turns into accurate, searchable text or into a pile of broken captions. Volume 5 covers the transcription pipeline in detail: recording and transcription architecture, timestamps and clock domains, jitter buffers that shape what reaches ASR, and incident triage by symptom. Written by Nikolay Sapunov, CEO at Fora Soft.
Adding call recording and transcripts without wrecking accuracy or storage costs?
We will review where your audio leaves the call and hand you a pipeline design covering branching, VAD segmentation, ASR choice and storage, with a cost estimate per recorded hour. 250+ video products shipped since 2005.
