Bavaria and its funny swearwords, lunch talk with colleagues, the Oktoberfest
What it does
This app solves an important societal integration challenge, that is, teaching non-Bavarians how to learn and correctly pronounce the many funny swearwords of the Bavarian language.
How I built it
An iOS app records voices and submits the voice data to a backend application where audio features are extracted and compared to original audio recordings. The best match is returned to the UI.
Challenges I ran into
- Acoustic Fingerprinting (Chromaprint algorithm) seems to work well for longer music but not so well for short voice audio snippets. MFCC (Mel Frequency Cepstral Coefficients – short-term power spectrum of a sound) and comparing the features using DTW (Dynamic Time Warping – measuring similarity between two temporal sequences) has then turned out to work quite well with speech samples.
- SwiftUI: Underestimated how fundamentally the way of building iOS UIs has changed in the most recent version of iOS/Swift
Accomplishments that I'm proud of
- Feature extraction and comparison of audio files
- A cool user interface with nice graphics created by our designer
What I learned
- Audio analysis algorithms and feature extraction from audio files
- New bavarian swearwords
What's next for Bavarian Swearword Trainer
Polishing and maybe App Store Release ;)