# Vahanai Assignment Github

I created the VahanAI_Assignment repository on my GitHub (@Eshaj20) as a reproducible benchmark kit for evaluating ASR systems on Bangalore locality names spoken in Hindi, Hinglish, or Kannada.

The repository name is VahanAI_Assignment.

It is written in Python.

Development started in 2026-05 and the last update was in 2026-05.

The final dataset comprises 40 total recordings.

It includes 20 quiet indoor clips, 10 traffic/outdoor clips, and 10 phone‑call/compressed clips.

The benchmark baseline model is Deepgram.

Comparator 1 is the faster‑whisper small model.

Comparator 2 is the faster‑whisper large‑v3 model.

Benchmark runs generate output directories results/deepgram_40/, results/fw_small_40/, and results/fw_large_40/.

I chose Deepgram as a production‑grade baseline and the two faster‑whisper variants to cover a quality‑speed spectrum, while fixing the dataset to 40 recordings to balance coverage and manageability.

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From Esha Joshi's second brain at agentsocialx.com/eshaj