Electronics and Communication + Data
Filter noise from an audio recording
Record speech with a hum, find the hum's frequency and remove it with a digital filter.
- DifficultyIntermediate
- Estimated time1–2 weeks
- Budget₹0
- ClassCollege
- TeamSolo or up to 2
- You needComputer only
Prerequisites: None beyond your class work
Original · by TechnifyedData AnalysisSoftware ProjectFree to doComputer onlyResearch orientedTwo subjects
Overview
Record speech with a hum, find the hum's frequency and remove it with a digital filter.
Skills you will use
Materials and tools
- Computer with a microphone
- Python
Tools and software
Step-by-step roadmap
Start
You will finish with: before-and-after audio and spectra with an explanation of the filter.
- 1
Prerequisites
Nothing special to know first. Then collect the 2 items in the materials list.
- 2
Learn
Read up on signal processing: audio, FFT, filtering. Your textbook chapter and one short video are enough.
- 3
Plan
List the features for version one, sketch the screens or data flow and pick the tools. Keep the first version small.
- 4
Build
- Record ten seconds of speech with a fan or mains hum.
- Plot the spectrum with a Fourier transform.
- Identify the noise frequencies.
- Design a notch or low-pass filter.
- Apply it and compare the spectra and the sound.
- 5
Test
Try it with wrong, empty and unusual input, and ask someone else to use it without your help.
- 6
Document
Write a README: what it does, how to run it, screenshots and what you learned. Report structure
- 7
Present
Show a live demo of one complete task, then the design and the hardest problem you solved. Presentation structure
- 8
Publish
Put the code on GitHub with the README and, if you can, deploy a live demo.
Expected outcome
Before-and-after audio and spectra with an explanation of the filter.
Other versions of this project
Advanced version
Implement spectral subtraction for broadband noise.
Ways to do this project
Text marked "You write this" is a prompt for your own work; everything else is specific to this project.
- Research question
- You write thisOne question you can answer with data, narrow enough to finish in the time you have.
- Hypothesis
- You write thisWhat you expect to find, and why.
- Variables
- You write thisWhat you change or compare, what you measure, and what you hold constant.
- Methodology
- You write thisDescribe the method in enough detail that someone else could repeat it: sample, tools, procedure.
- Data collection
- You write thisSay what you will record, how many times, and how you will keep the records safe.
- Analysis
- You write thisChoose the table, chart or test that answers the question; report averages with their spread.
- Limitations
- You write thisList what could have affected the result: small sample, instrument limits, things you could not control.
Literature review
Find five to eight sources (your textbook, review articles, reports) and note what each says about your question. Group them by idea, not one after another, and end with what is still not known.
References
List every source you used in one style throughout (author, year, title, where it was published, link and the date you opened it).
Use this as the outline of your README or case study.
- Problem
- You write thisThe problem in one or two sentences.
- Why it matters
- You write thisWho has this problem and what it costs them.
- What was built
- Before-and-after audio and spectra with an explanation of the filter.
- Technology
- NumPy, Python
- Architecture
- You write thisOne diagram: the parts and how data moves between them.
- Implementation
- You write thisThe 5 build steps in your own words, with one code or design decision you are proud of.
- Challenges
- You write thisThe hardest bug or decision, and how you got past it.
- Results
- You write thisNumbers: accuracy, speed, users, survey answers.
- Demo and code
- You write thisA link to a live demo or a short video, and to the GitHub repository.
- Lessons learned
- You write thisWhat you would do differently next time.
- Future improvements
- Implement spectral subtraction for broadband noise.
- Problem
- Record speech with a hum, find the hum's frequency and remove it with a digital filter.
- Target user
- You write thisOne specific person: who they are and when they would use this.
- Solution
- Record speech with a hum, find the hum's frequency and remove it with a digital filter.
- First version (MVP)
- You write thisThe smallest version that shows the idea working once, end to end.
- Tech stack
- NumPy, Python
- Architecture
- You write thisA quick sketch of the parts and how they connect.
- Demo
- You write thisThe one scenario you will show live, start to finish, in under two minutes.
- Stretch goals
- Implement spectral subtraction for broadband noise.
Team roles
Plan by length
24-hour
- Hours 0–2: agree the problem, the user and the one thing the demo must show
- Hours 2–16: build only the first version
- Hours 16–20: test the demo path end to end and fix what breaks
- Hours 20–24: slides, a 2-minute demo script and a backup recording
48-hour
- Evening 1: problem, user, sketch and task split
- Day 1: first version working end to end
- Day 2 morning: one stretch goal and testing
- Day 2 afternoon: polish, slides and demo practice
1-week
- Day 1: research the problem and talk to two possible users
- Days 2–4: first version
- Day 5: stretch goals
- Day 6: testing and write-up
- Day 7: demo video and presentation
Working as a team
Solo or up to 2. Suggested roles:
Report and presentation
Report structure
- Title and summary
- Problem and target user
- Features
- Tools and technology
- Design: architecture, data model or screens
- Implementation
- Testing
- Results and screenshots
- Challenges
- Future improvements
- References
Presentation structure
- The problem
- Who it is for
- Live demo
- How it is built (one diagram)
- The hardest part
- Testing and results
- What you learned
- What comes next
Viva questions
Prepare your own answers to these before you present.
- What is the aim of your project, in one sentence?
- What is the principle behind it?
- Why did you choose these materials or tools?
- What result did you get, and was it what you expected?
- What went wrong and how did you fix it?
- How could this be improved or used in real life?
Resources
Source and attribution
Original
Written by Technifyed. Free to use for your own school or college project; write the report in your own words. Added 1 Oct 2026.
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