Cases of scam or fraudulent phone calls have been escalating all around the world. In the US, the consumers fend off more than 3b scam calls a month with Americans losing $30b to scam calls in the first half of 2021 alone. In Singapore itself, the reported number of scam calls in first half of 2022 spiked to 13,000 cases, an increase of almost 100% over the previous year. The total sum lost to scam calls amount to $347m. According to a consumer report, almost 90% of Singapore consumers have received scam calls. What is interesting in the finding is that 75% continue to pick up the calls, despite the extensive coverage of this issue in the mainstream media.
Spam calls are very difficult to prevent despite the efforts of the authorities and telcos. The scammers always manage to find ways to circumvent for their next round for every solution that the authorities apply. It can be said that it is a proverbial dog chasing the tail problem. Nonetheless, there will continue to be efforts to try to solve this problem.
In this project, we aim to find ways to detect fraudulent phone calls before they pick up or while they are still taking and alerting the user. We plan to perform the detection using voice prints, robotic voice identification as well as using machine learning on the phone content. We will develop an app that will give access to the call to perform recognition and therefore alert the users.
Research previous work and Data Collection
Exploratory Data Analysis
Pre-processing and Augmentation
Model Analysis and Interpretation. Week 9-10: App Development
The participants will be exposed to the complete pipeline of machine learning development from conception to app development