{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreieme6gjf4ygolnuzwvp6midgdx4n2lxqcnhwhvuytudy5fazfudvm",
    "uri": "at://did:plc:lk3jfj3zq4k4wxnk474axylu/app.bsky.feed.post/3mmvzk6z44zn2"
  },
  "path": "/t/how-to-sync-dual-channel-transcripts-via-openai-whisper-vad-silence-stripping-destroys-absolute-timestamps/1381942#post_2",
  "publishedAt": "2026-05-28T10:54:31.000Z",
  "site": "https://community.openai.com",
  "textContent": "Well honestly your split-channel approach is actually pretty solid already  the timestamps/speaker reconstruction logic looks mostly correct to me.\n\nThe bigger issue feels more like Whisper struggling with\n\n  * narrowband 8kHz telephony audio\n\n  * overlapping speech/interruption handling\n\n  * and context reconstruction across independently transcribed channels.\n\n\n\n\nA few things stand out from your output tho\n\n  * “Policy Test” instead of “caller side test”\n\n  * numbers normalized weirdly\n\n  * sentence continuation split oddly across timestamps\n\n  * interruption timing drift around the “blue” overlap\n\n\n\n\nSo that usually looks more like ASR inference limitations than AGI/Asterisk sync problems.\n\nOne thing I’d seriously test\n\n  * upsample audio to 16kHz before transcription (`sox` or `ffmpeg`)\n\n  * even though no new information is created, Whisper tends to behave noticeably better on resampled telephony audio.\n\n\n\n\nAlso maybe try\n\n  * adding small silence padding at start of both legs before transcription\n\n  * forcing shorter segments/VAD chunking\n\n  * aligning merged segments by midpoint timestamps instead of raw start times only.\n\n\n\n\nHmm.. Your actual synchronization pipeline honestly seems cleaner than most PBX transcription setups I’ve ever seen",
  "title": "How to sync dual-channel transcripts via OpenAI Whisper (VAD silence stripping destroys absolute timestamps)"
}