Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM57143

Sound Snap – AI-Powered Audio-To-Midi Conversion Platform

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM57143

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

DJT

Darshan Jibhau Thakare

RBN

Raj Bharat Nemade

TPM

Tanmay Prashant Mohan

JSP

Jayesh Suresh Patil

MSSP

Ms. S. S. Pathare

Author Services & Downloads

Full Articles

Abstract

Currently, audio-to-MIDI conversion is often performed using complex Digital Audio Workstations (DAWs) or offline transcription tools that require manual processing, advanced technical knowledge, and significant computing resources. While several software solutions provide audio transcription capabilities, many lack real-time feedback, web accessibility, and seamless playback integration. Additionally, traditional workflows involve multiple steps such as exporting audio, running conversion software separately, manually importing MIDI files into players, and configuring instrument packs. These processes are time-consuming, error-prone, and not user-friendly for beginners or musicians seeking quick results. The proposed system, Audio to MIDI Studio, offers a modern and automated web-based solution for converting audio recordings into MIDI files using Spotify’s Basic Pitch model. The application enables users to record audio directly in the browser or upload existing audio files. The backend processes the audio using an asynchronous job pipeline built with FastAPI, where the audio is preprocessed, normalized, and transcribed into MIDI format. The system provides real-time job status updates using WebSocket communication, ensuring a responsive user experience. Once transcription is complete, the generated MIDI file can be played directly in the browser using html-midi-player, with selectable SoundFont instrument packs. Users can also download the MIDI file for further editing or production use. This automated workflow reduces manual effort, eliminates dependency on complex desktop tools, and provides a fast, secure, and efficient method for audio-to-MIDI transcription. By integrating modern web technologies with machine learning-based transcription, Audio to MIDI Studio delivers a production-ready, scalable, and user-friendly solution for musicians, educators, and developers.

KEYWORDS

Audio to MIDI conversion Basic Pitch FastAPI WebSocket MIDI playback real-time transcription web-based music processing.

Cite This Article

Darshan Jibhau Thakare, Raj Bharat Nemade, Tanmay Prashant Mohan, Jayesh Suresh Patil, Ms. S. S. Pathare, "Sound Snap – AI-Powered Audio-To-Midi Conversion Platform," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026.

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

3/2/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

2

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...