case study

Cloud9 Technologies

Specialty Speech Recognition

Banking & Financial Services

Business Impacts


Accuracy for number transcriptions


Accuracy for trading parameter transcriptions

Customer Key Facts

  • Location : North America
  • Industry : Technology



  • Overlapping speech data
  • Transcription of financial jargons
  • Lack of labeled data
  • 5-10 seconds of trade “shouts” in multiple accents

Technologies Used





Google ML Engine

Google ML Engine

Monitoring Financial Trader Behavior with a Domain-Adapted Speech Recognition Model


Quantiphi built a state-of-the-art speech recognition model for monitoring financial trader behavior. The custom Automated Speech Recognition (ASR) helped to accurately transcribe trader conversations with financial jargon and domain-specific terms to text.

Cloud9 Technologies also uses Quantiphi to inject powerful analytics into its platform driven by the data collected, providing users with the vital information they need on the trading floor. This includes text analytics-driven insights for frequently traded commodities, active buyers, purchased stocks, and more, further enhancing relationships with traders.


  • Better monitoring of trader behavior through domain-adapted custom speech recognition
  • Speech transcriptions with near human level accuracy
  • Streamlined and simplified storage of exceptionally large data volumes

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