How do I set up call recording software for real-time transcription and speaker diarization on sales calls?

Here’s a practical way to set up call recording software for real-time transcription and speaker diarization on sales calls.

1) Pick a recording/transcription stack

You generally need three parts:

1. Call recording capture

   • Zoom / Google Meet / Microsoft Teams recording
   • VoIP phone system integration (e.g. RingCentral, Dialpad, Aircall, Zoom Phone, Twilio)
   • A local desktop app or browser extension if your platform allows it

2. Speech-to-text transcription

   • Real-time or near-real-time ASR engine
   • Examples: OpenAI Whisper-based services, Deepgram, AssemblyAI, Google Speech-to-Text, AWS Transcribe

3. Speaker diarization

   • Identifies and labels who spoke when
   • Often available in the same API/service as transcription, or as a separate model
   • Common providers: AssemblyAI, Deepgram, Google, AWS, pyannote.audio

For sales calls, it’s usually easiest to use a provider that offers both transcription and diarization in one API.

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2) Choose an implementation approach

Option A: Use a ready-made sales call platform

Best if you want fast setup with minimal engineering.

Examples:

• Gong
• Chorus
• Avoma
• Fireflies
• Otter
• Fathom

These often provide:

• Automatic recording
• Live transcript
• Speaker labels
• CRM sync
• Call summaries and coaching

Option B: Build your own pipeline

Best if you need full control.

Typical architecture:

• Audio source: meeting platform or phone system
• Stream audio to your backend
• Transcription service processes audio in real time
• Diarization model segments speakers
• UI/dashboard shows live transcript with speaker labels
• Storage saves audio, transcript, and metadata
• CRM integration pushes notes to Salesforce/HubSpot

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3) Set up call capture

Make sure your call source supports recording or audio streaming.

For meetings

• Enable recording in Zoom/Teams/Google Meet
• Use a bot participant or native integration if available
• Confirm consent settings and announcements

For phone calls

• Use a cloud telephony provider:
  • Twilio Voice
  • Dialpad
  • Aircall
  • RingCentral
• Enable call recording or media streaming
• If using Twilio, use Media Streams to send audio to your server in real time

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4) Send audio to transcription in real time

Your backend should:

• Receive live audio chunks
• Normalize audio format if needed:
  • Mono
  • 16 kHz sample rate is common
  • PCM/WAV often preferred by APIs
• Send audio to the transcription API via websocket or streaming endpoint

Important tips

• Keep latency low by chunking audio into small frames
• Use a stable network connection
• Buffer a few seconds to avoid dropped words
• Handle partial transcripts and final transcripts separately

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5) Add speaker diarization

Speaker diarization can be handled in two ways:

A. Built-in diarization from your transcription provider

Simplest:

• The API returns transcript segments with speaker labels like Speaker 1 / Speaker 2
• You map those speakers to “rep” and “customer” if possible

B. Separate diarization model

Useful if your transcription service doesn’t support it.

Common flow:

1. Run diarization on the audio
2. Get speaker time ranges
3. Align transcript words or segments to those time ranges

Practical note

In sales calls, diarization is often good enough to distinguish rep vs prospect, but not always perfect. The first few seconds of each speaker help the model adapt.

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6) Build the live transcript UI

A useful sales-call transcript view usually shows:

• Speaker name/label
• Timestamp
• Live transcript text
• Confidence score if available
• Highlights for objections, pricing mentions, next steps, competitors

Optional:

• Real-time note-taking
• Keyword alerts
• Sentiment or talk-time analytics
• CTA/objection tracking

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7) Store and sync the data

Save:

• Audio file
• Raw transcript
• Speaker turns
• Call metadata:
  • date/time
  • participants
  • account name
  • deal ID
  • CRM contact/opportunity

Then sync to:

• Salesforce
• HubSpot
• Outreach
• Salesloft

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8) Consent and compliance

This is important.

Before recording sales calls:

• Check local call-recording laws
• Determine if you need one-party or two-party consent
• Add a verbal or automated disclosure at the start of the call
• Update privacy policy and internal retention rules
• Secure recordings and transcripts with access controls

If you sell in multiple regions, apply the strictest applicable policy.

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9) Recommended technical choices

If you want a straightforward build:

Fastest reliable stack

• Capture: Twilio / Zoom / Teams integration
• Transcription: AssemblyAI or Deepgram
• Diarization: same provider if supported
• Backend: Node.js or Python
• Storage: S3/GCS + Postgres
• UI: React dashboard
• CRM sync: Salesforce/HubSpot API

If you want open-source

• Transcription: Whisper
• Diarization: pyannote.audio
• Audio pipeline: WebSocket streaming + Python backend
• More control, but more engineering and tuning

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10) A simple rollout plan

1. Start with one call platform
2. Enable recording and consent disclosure
3. Integrate live transcription
4. Turn on diarization
5. Test with 10–20 calls
6. Review speaker accuracy and transcription errors
7. Tune audio quality and labeling
8. Push summaries and notes into CRM

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11) Common pitfalls

• Poor audio quality from conference bridges
• Echo / crosstalk causing diarization mistakes
• Recording without proper consent
• Not separating final vs partial transcript events
• Latency too high for “real-time” use
• No fallback if the transcription API fails

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If you want, I can give you:

1. a recommended vendor stack,
2. a step-by-step Twilio + transcription API setup, or
3. a sample architecture diagram / code outline.