I am a Data Scientist and a Masters Candidate - Computational Linguistics at Universität Stuttgart. I am currently researching on Speech, Language and Vision methods for extracting value out of unstructured data.
In my previous stint with Deloitte Consulting LLP, I worked with Fortune Technology 10 clients to help them make data-driven (profitable) decisions. In my surplus time, I served as a Subject Matter Expert on Google Cloud Platform to help build scalable, resilient and fault-tolerant cloud workflows.
Before this, I have worked with startups across India to build Social Media Analytics Dashboards, Chat-bots, Recommendation Engines, and Forecasting Models.
My core interests lie in Natural Language Processing, Machine Learning/ Statistics and Cloud based Product development.
Apart from work and studies, I love travelling and delivering Workshops/ Talks at conferences and events across APAC and EU, DevConf.CZ, Berlin Buzzwords, DeveloperDays Poland, PyCon APAC (Philippines), Korea, Malaysia, Singapore, India, WWCode Asia Connect, Google DevFest, and Google Cloud Summit.
@reach_vbInstitute / Company –
University of Stuttgart
The audio (& speech) domain is going through a massive shift in terms of end-user performances. It is at the same tipping point as NLP was in 2017 before the Transformers revolution took over. We’ve gone from needing a copious amount of data to create Spoken Language Understanding systems to just needing a 10-minute snippet.
This tutorial will help you create strong code-first & scientific foundations in dealing with Audio data and build real-world applications like Automatic Speech Recognition (ASR) Audio Classification, and Speaker Verification using backbone models like Wav2Vec2.0, HuBERT, etc.