Blue Machines AI Launches BFSI Speech Model Aurora
Blue Machines AI has launched Aurora, a speech-to-text model designed for banking, financial services and insurance (BFSI) conversations in India.
The model targets financial conversations where customers switch between English and regional languages, use industry-specific terminology and communicate over noisy or low-bandwidth telephone connections. Blue Machines AI said internal evaluations recorded a 1.51% Semantic Word Error Rate (WER) for English, 2.43% for Hindi BFSI conversations and 5.52% across multilingual speech.
Aurora also recorded a 4.23% BFSI Entity Error Rate for information including monetary amounts, interest rates, policy numbers, account references and transaction IDs.
Built For Financial Speech
The model was evaluated against leading speech-to-text models using consistent audio inputs and scoring methods, according to Blue Machines AI.
The datasets covered banking, lending, insurance, collections and customer service. They included Indian English, Hindi, Hinglish, multilingual and code-mixed speech, along with regional pronunciation patterns, background noise and telephony audio.
The model is...
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