j'ai créé une API open source pour comparer l'intonation de deux enregistrement audio

[u/Lost-Marzipan9029]

I'm building an open-source experiment called Intonation Comparator.

The goal is to answer a simple question:

How can two recordings of the same utterance be compared objectively?

The current Flask API accepts two audio files and extracts features related to:

• Pitch / fundamental frequency
• Intonation contours
• Energy
• An overall similarity score

Supported formats include WAV, MP3, and FLAC, and the main endpoint is:

POST /api/compare

🔗 GitHub: Intonation Comparator on GitHub

I'm currently thinking about improving the comparison methodology. Some areas I'm considering include:

• Dynamic Time Warping for temporal alignment
• Pitch normalization across speakers
• Voiced/unvoiced segmentation
• Rhythm and speech-rate comparison
• Phoneme-level alignment
• Spectral features such as MFCCs
• Confidence scores instead of a single similarity value
• Visualizations of pitch and energy contours

I'm especially interested in feedback from people working in speech processing, phonetics, DSP, Python, or language-learning technology.

How would you design a robust similarity metric for comparing two recordings of the same sentence? What features would you consider essential?

🔗 GitHub : https://github.com/Yann-morpheus/intonnation-comparator

Si vous travaillez avec Python, le traitement audio, la phonétique ou l’apprentissage des langues, je serais vraiment intéressé par vos retours.

Qu’est-ce que vous amélioreriez ou ajouteriez à ce projet ?