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@article{197955,
        author = {Prabha Gawde and Surabhi Talekar and Sayali Landge and Pruthvi Patil and Prof. Archana Salaskar},
        title = {Interview success with AI assistance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {10032-10037},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197955},
        abstract = {Getting ready for interviews is something most students have to deal with at some point, especially when campus placements come around. While mock interviews and coaching sessions do help, not every student has access to them — costs can be high and finding the time is another challenge altogether. On top of that, the kind of feedback a student receives tends to vary from one interviewer to another, making it hard to track whether any real improvement is happening.
We built a fairly straightforward AI-based mock interview system that lets students rehearse on their own, without needing anyone else in the room. The system records both video and audio during a session. It looks at the candidate's facial expressions through the video feed, and separately converts what they say into text to check how relevant their answers are. All of this gets pulled together into a single performance score at the end.
We weren't trying to replicate a real interview panel — the goal was simply to give students a reliable way to practice and get a sense of where they stand. Even with a relatively basic setup, the system turned out to be useful for giving candidates a clearer picture of their overall performance.},
        keywords = {mock interview, sentiment analysis, facial expression recognition, performance score, artificial intelligence.},
        month = {April},
        }