Blue Machines AI launches BFSI-focused speech-to-text model Aurora

Blue Machines AI has launched Aurora, a multilingual speech-to-text model designed specifically for banking, financial services and insurance (BFSI) conversations in India.

The model is built to process real-time conversations involving Indian English, Hindi, Hinglish and other multilingual and code-mixed speech, including interactions over noisy or low-bandwidth telephone connections.

According to internal benchmarks conducted by Blue Machines AI on BFSI datasets, Aurora recorded a Semantic Word Error Rate (WER) of 1.51% for English, 2.43% for Hindi BFSI conversations and 5.52% across multilingual speech. It recorded a BFSI Entity Error Rate of 4.23% for information including monetary amounts, interest rates, policy numbers, account references and transaction IDs.

The company said the datasets used for testing covered banking, lending, insurance, collections and customer servicing, and included regional pronunciation patterns, background noise and telephony audio.

Aurora has been trained to recognise financial terminology and entities such as EMIs, outstanding amounts, foreclosure charges, disbursals,...

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