Your question is ASR and ML Fundamentals. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Describe some ASR and ML concepts.
Cover the ASR pipeline, including acoustic modeling, language modeling, decoding, CTC, sequence-to-sequence models, and beam search. Explain how you would evaluate an ASR system using WER and related metrics, then connect those choices to broader ML concepts such as loss functions, overfitting, model selection, and error analysis. Be prepared to discuss practical tradeoffs between accuracy, latency, compute cost, and robustness.