I have a recorded interview in urdu that needs to be handled end-to-end. First, I need a verbatim transcript of the entire session in both Urdu and English , delivered as a clean .word file with clear speaker tags and time stamps at reasonable intervals so I can reference key moments quickly. Once the text is ready, I’d like you to move straight into coding the data analysis and visualization. Think sentiment trends, word frequencies, keyword clouds, and any other insightful patterns you can surface from the conversation. Python is my usual go-to, so libraries such as pandas, nltk or spaCy for processing, and matplotlib or seaborn for the visuals will fit nicely—though I’m open to whatever stack you prefer as long as the final scripts run reproducibly on a standard environment. Deliverables: • Full transcript word format with speaker labels and time stamps • Well-commented code files that parse the transcript, perform the analysis, and generate the visuals • A short README explaining how to run everything and what each chart represents Everything should be tidy, reproducible, and ready for me to drop into my existing workflow. Let me know your timeline and any clarifying questions you need answered before we kick off.