Stereo recordings are everywhere, from contact center calls to doctor-patient conversations. The challenge is turning both sides into one useful transcript.
Until now, there were two common approaches:
🔹 Split the channels, run two recognition sessions, and merge the results in post-processing.
🔹 Mix the audio down to mono and use speaker diarization to separate speakers.
Real-time multichannel speech-to-text adds a new, optimized option: keep the stereo input in one continuous session. Every result is tagged with its source channel, so there’s no post-processing needed to merge transcripts.
In this demo, we run a contact center conversation through all three modes side by side and compare the results:
✅ Stronger handling of overlapping speech than mono + diarization
✅ Simpler orchestration, with one session and no merge step
✅ Lower processing cost: split-channel processing costs about twice as much
✅ Can be combined with speaker diarization when a channel has more than one speaker
Learn more: https://msft.it/6053aoObb
#AzureSpeech #MicrosoftFoundry #SpeechToText
