Morgan Stanley Services Group Inc.

Aratrika Sarkar

Mehak Mehta

Cheryl Fernandes

Melissa Kagaju

Mayank Jain

Sushil Ninawe

Ayyapparaj Radhakrishnan Ganesan

Jayati Tripathi

A device, system and method for analyzing audio speech signals to detect fraudulent calls to a contact center comprising splitting an audio recording of a call in real-time into a foreground speech signal attributed to a main speaker and a background audio signal, extracting audio features from the foreground speech signal and background audio signal, inputting the extracted audio features into an ensemble model comprising multiple different machine learning models co-trained to cumulatively detect fraud, wherein the multiple different machine learning models include: a speaker audio model to detect audio speech anomalies, a speaker intent model to classify intent of the main speaker, a synthetic voice detection model to identify a non-human entity, and a prosody model to detect voice intonation of the main speaker. A prediction may be output, by the ensemble model, indicating whether the call is fraudulent.

Audio speech signal analysis for fraud detection

A device, system and method for analyzing audio speech signals to detect fraudulent calls to a contact center comprising splitting an audio recording of a call in real-time into a foreground speech signal attributed to a main speaker and a background audio signal, extracting audio features from the foreground speech signal and background audio signal, inputting the extracted audio features into an ensemble model comprising multiple different machine learning models co-trained to cumulatively detect fraud, wherein the multiple different machine learning models include: a speaker audio model to detect audio speech anomalies, a speaker intent model to classify intent of the main speaker, and a prosody model to detect voice intonation of the main speaker. A prediction may be output, by the ensemble model, indicating whether the call is fraudulent.

A system and method for creating accessibility of any website or application for people with sight, hearing or speech disabilities. The system and method can include receiving input of the website or the application to be accessed and an indicator as to specific disabilities a user, scoring the website or the application for its accessibility based on the specific disabilities of the user, and if the score is below a threshold, determining an alternative form for the input of the website or the application to accommodate the specific disabilities of the user.

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Jersey City, NJ, United States of America

Aratrika Sarkar