Bengaluru, Karnataka, India
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About

As a Data Engineer with 5+ years of experience, I specialize in designing and managing…

Articles by Aman

  • My first internship | CDAC
    Jul 31, 2018

    My first internship | CDAC

    Keywords: CDAC, SCADA, Networking and Communication, Socket Programming, Cyber Security, Communication Protocols, Human…

  • What you see Vs What you should see
    Jun 9, 2018

    What you see Vs What you should see

    Before going through the article I would like you to go through this Forbes article by Niall McCarthy(original work…

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Experience & Education

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Licenses & Certifications

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Volunteer Experience

Publications

Courses

  • Embedded Systems

    EC381

  • Data Structure

    CS103

  • Database

    -

  • Operating Systems

    CS231

Projects

  • Voice Enabled Personalized Recommendation System

    -

    Voice Enabled Personalized Recommendation System is a kind of Speaker Identification System combined with Speech Recognition. The problem is focused on identifying the speaker and executing the command of what the speaker is uttering. The system requires limited data-set in the form of training speech corpus. The process of executing this project involves a survey for speech data, prepossessing the data for anomalies, and extracting feature using Mel-frequency Cepstral coefficients (MFCC). The…

    Voice Enabled Personalized Recommendation System is a kind of Speaker Identification System combined with Speech Recognition. The problem is focused on identifying the speaker and executing the command of what the speaker is uttering. The system requires limited data-set in the form of training speech corpus. The process of executing this project involves a survey for speech data, prepossessing the data for anomalies, and extracting feature using Mel-frequency Cepstral coefficients (MFCC). The features are then fed into two different classifying algorithms namely Gaussian Mixture Model (GMM) and Support Vector Machine (SVM) for training the speaker recognition model. The accuracy of the proposed models is tested for different sizes of MFCC feature vector after fine-tuning the GMM and SVM models. Care has been taken to test the accuracy of the proposed models for different sizes of MFCC feature vector on fine-tuning GMM and SVM models. The proposed experimental setup with a frame overlap of 75% and MFCC feature size of 20-MFCC + 20-∆MFCC + 20-∆∆MFCC coefficients perform better on SVM than GMM. These speaker identification experiments were tested using the speech corpus collected from the Voxforge website. The diversity in the speech corpus shows that the method performs equally well irrespective of language, gender, age, and region.

    See project

Honors & Awards

  • Ace Alliance

    Flipkart

    Reward Name
    Ace Alliance

    About Reward
    Quarterly Award: Teams who collaborated in cross-functional projects, successfully showcasing a Flipkart first behavior; acted towards achieving one another's goals

    Message from the leader:
    Joint Risk Model 2.0 is our biggest bet for democratizing credit cards. The objective of this project was to widen the base to which we offer the co-brand credit card and also increase the conversion post-application. And to do this we had to…

    Reward Name
    Ace Alliance

    About Reward
    Quarterly Award: Teams who collaborated in cross-functional projects, successfully showcasing a Flipkart first behavior; acted towards achieving one another's goals

    Message from the leader:
    Joint Risk Model 2.0 is our biggest bet for democratizing credit cards. The objective of this project was to widen the base to which we offer the co-brand credit card and also increase the conversion post-application. And to do this we had to replace the existing 3-year-old white-listing methodology with the new one that is built on 100+ Flipkart variables. It was a project of a mammoth scale with teams across CRI, Eng, Insights, Product, and Business coming together to work with Axis Bank to make this happen. The early results are encouraging with the Whitelist base increasing by 30%, IPA by 15%, and the Income Document waiver by 35-40%. Kudos to the team that brought us closer to our vision of democratizing credit using Flipkart data.

  • Essay Competition, Paryatan Parv(Ministry of tourism, India)

    Indian Institute of Information Technology Senapati

    2nd Position
    The topic was "Eco-Tourism".

  • Painting Competition, Paryatan Parv(Ministry of tourism, India)

    Indian Institute of Information Technology Senapati

    1st Position
    The topic was "Poster making on Tourism".

  • Photography / Slide show Competition, Paryatan Parv(Ministry of tourism, India)

    Indian Institute of Information Technology Senapati

    1st Position
    The topic was "Any tourist spot from Madhya Pradesh". I presented on "Pachmarhi". LISTED IN UNESCO BIOSPHERE RESERVE FOR ITS FLORA AND FAUNA.

  • My earth My Story Contest

    Gov of India, Mahindra Samriddhi India Agri Award

    It was a photography plus an innovative farming idea contest at the national level. Among all around India, I was positioned in top five. Won cash prize and an entry in Mahindra Samridhhi India Agri Award.

    https://youtu.be/_XQxLC9HOig

Test Scores

  • TRACK Test

    Score: A1

    Tracktest.eu is an independent provider of English language tests. Tracktest.eu uses the
    widely recognized and well established grading system (CEFR) defined by the Council of
    Europe. Test ID:158157

Languages

  • English

    Professional working proficiency

  • Hindi

    Native or bilingual proficiency

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