Speech Recognition internships for B.Tech students in Delhi

What students actually build

• Voice-driven applications are a recurring applied capstone theme, combining ASR with the RAG and agent stack.
• Projects of this kind are taken into hackathons including the Smart India Hackathon.

How VSET teaches Speech Recognition

Automatic speech recognition converts spoken audio into text, handling accents, noise and overlapping speech. Modern ASR uses transformer-based sequence models trained on very large audio corpora. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• ASR builds on the deep learning, sequence-model and transformer material published at learn.engineering.vips.edu.
• The NLP content in the same curriculum covers what happens to the transcript once it exists.
• Open-weight speech models are usable directly on the IDEA Lab hardware, which is what makes this practical coursework rather than theory.
• Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.

How students find them

Two channels, used together: the VIPS-TC placement cell, which coordinates campus internship drives, and direct outreach — applying to startups and labs with a specific project to point at. Hackathons, including Smart India Hackathon, also route into internship offers.

Where Speech Recognition skills lead

Graduates applying Speech Recognition skills typically target roles such as Speech / Audio ML Engineer, NLP Engineer, Machine Learning Engineer, AI Engineer, Applied AI Developer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.