Normalize Recruiter Transcript Text | Dataford Interview Questions

Given a list of transcript strings, write a Python function clean_transcripts(lines) that returns a new list of cleaned strings. For each line, convert text to lowercase, trim leading and trailing whitespace, collapse repeated internal whitespace into a single space, remove filler tokens "um", "uh", and "like" when they appear as whole words, remove non-alphanumeric characters except spaces, and discard empty results. After cleaning, remove duplicate lines while preserving the first occurrence order.

Constraints

1 <= len(lines) <= 10^4
0 <= len(lines[i]) <= 10^3
Each input element is a string
Filler removal is case-insensitive and applies only to whole words

Function Signature

def clean_transcripts(lines):

Your question is Normalize Recruiter Transcript Text. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Constraints

1 <= len(lines) <= 10^4
0 <= len(lines[i]) <= 10^3
Each input element is a string
Filler removal is case-insensitive and applies only to whole words

Function Signature

def clean_transcripts(lines):

Your question is Normalize Recruiter Transcript Text. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.