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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
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Total Authors : 22487
Total Reviewer : 811
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Published Paper Details
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| Paper Title: | End To End AI Video |
| Authors Name: | Shruti Pradip Waghaye , Shravani Sanjay Lende , Sakshi Nimbarte[ , Shejal Deogade , Bhushan Nagarkar |
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| Author Reg. ID: |
IJRTI_203457
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| Published Paper Id: | IJRTI2505074 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | The adoption of end-to-end AI technologies in video interviews is rapidly reshaping the recruitment landscape by automating the evaluation of candidates. These sophisticated systems integrate computer vision, natural language processing, and machine learning techniques to assess diverse factors of a candidate's interview performance, such as speech clarity, facial expressions, and body posture. Through the examination of speaking patterns, emotional undertones, and behavioral signals, AI tools provide recruiters with comprehensive insights into a candidate’s communication effectiveness, self-confidence, and overall suitability for specific roles. AI-driven video interview platforms enhance the efficiency of hiring processes by expediting initial screenings, enabling faster decision-making, and minimizing subjective biases. These platforms are capable of processing and analyzing large volumes of candidate data simultaneously, delivering precise, evidence-based evaluations to help identify the most qualified individuals. Moreover, they enrich the candidate experience by offering immediate feedback and ensuring fairness and consistency across assessments. Nevertheless, the implementation of such AI solutions also raises critical issues, including safeguarding privacy, securing data, and mitigating biases within algorithmic systems. Ensuring that AI decisions are transparent and easily interpretable is vital to uphold trust between applicants and organizations. This abstract discusses the operational capabilities, benefits, and potential challenges associated with end-to-end AI video interview platforms, highlighting their transformative influence on modern hiring strategies and the future of AI-led recruitment practices |
| Keywords: | HCR (Handwritten Character Recognition), QBT (Query By Text), QBS (Query By String), DTW (Dynamic Time Warping), ICA (Independent Component Analysis). |
| Cite Article: | "End To End AI Video", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a630-a635, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505074.pdf |
| Downloads: | 000413 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505074
Registration ID:203457
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a630-a635 Country: Bhandara, Maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505074 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505074 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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