dejavu
Audio fingerprinting and recognition in Python (by worldveil)
matchering
🎚️ Open Source Audio Matching and Mastering (by sergree)
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dejavu | matchering | |
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15 | 4 | |
6,308 | 1,198 | |
- | - | |
0.0 | 3.9 | |
8 months ago | 3 months ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dejavu
Posts with mentions or reviews of dejavu.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-14.
- Audio Fingerprinting and Recognition in Python
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Contacting Collectors or Creating API to help with searching
This doesn't seem hard, you can use something like this to dwoanload the songs: https://stackoverflow.com/a/27481870/6151784 and something like this to calculate how much they match: https://github.com/worldveil/dejavu The question is would you create a (dedicated) server to do your work? Or your own pc? You could also create a very simple page where someone would paste you a YouTube profile URL and you would check all songs of this URL. Also to have a db and save information about the matching and which youtube profiles have alsready been checked. Something like that could work.
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Tiny bit of experience but need to compile a Github program. What is the best video / resource to learn to do this quickly?
If you read the installation.md file it clearly states that it has only been tested on UNIX systems, so you might be on your own trying to get it to wor in windows.
- Help needed with school project
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Identification of all usages of OSTs in Made in Abyss (S1)
Using neural networks seems complicated, did you tried audio fingerprinting? I have been using this audio fingerprinting library to power this anime song synchronization script. You can check Panako and dejavu too.
- Dejavu – Audio fingerprinting and recognition algorithm
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fingerprinting sections of audio from file
I want to say these few seconds match these few seconds from a different audio track. Using dejavu raw has overhead I do not need/want and hence I've been fiddling around with the fingerprint script. When modifying the global variables I can get better hits or worse hits, I will admit that even after reading there recommended article and many other sources, I can't find some good explanations about the mathematics behind the filtering after the specgram has been applied. As far as a I am aware we first apply filters to find/make fine points across the spectrogram after that we only check the distance between points along the time axis not the frequency or a hypotenuse (weird).
- Some information and advice about DDoS, from someone who was there during #opPayback
- List of resources
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Uploading an audio dataset into a database for comparison
I used a repo called https://github.com/worldveil/dejavu to compare audio hashed fingerprints and distinguish the difference between them.
matchering
Posts with mentions or reviews of matchering.
We have used some of these posts to build our list of alternatives
and similar projects.
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Top 10 AI Mixing and Mastering Tools for Musicians
Songmastr is a web-based AI mastering tool. Utilizing the power of the open-source Python library called Matchering, Songmastr is able to create a masterful audio track that matches a reference song of your choosing. The algorithm studies the RMS, FR, peak amplitude and stereo width of your reference track before applying it to the target audio file.
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what am I doing wrong? 😞
Ever tried matching ? I really dig that tool: https://github.com/sergree/matchering
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Automatic Reference Mastering Website
I made an automatic mastering website (www.songmastr.com) using the open source software Matchering (all credit to them). I have no users for the meantime, so I'd be happy to get some feedback ! How it works: 1 - You upload your song 2 - You chose a reference for mastering from the catalog / or you upload your own 3 - That's it ! Download the result. The matchering algorithm tries to match frequency response, RMS, peak amplitude and stereo width. The goal is not to replace professional mastering, but rather to offer a quick way to get your demo, or home recording in the same ballpark as commercial songs. Is it free ? - The link below gives out 5000 credits to the first users to claim them - After that, I plan on offering 2-3 free masters per week. Users that need more intensive server use can purchase credits Try it out: https://www.songmastr.com/?oip=eNoztTAx0zM1MjDRs7C0NNAzMjc2BgAmiwPW Have a nice day,
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Mastering Plugin
Re: Matchering (https://github.com/sergree/matchering), here is a little more information. If I recall correctly there is a docker-ized version so you can run it locally relatively easily if you are willing to learn a couple of bash commands. I have not played with it a lot and it is separate from the DAW.
What are some alternatives?
When comparing dejavu and matchering you can also consider the following projects:
django-elastic-transcoder - Django + AWS Elastic Transcoder
pydub - Manipulate audio with a simple and easy high level interface
m3u8 - Python m3u8 Parser for HTTP Live Streaming (HLS) Transmissions
librosa - Python library for audio and music analysis
audiolazy - Expressive Digital Signal Processing (DSP) package for Python
pyAudioAnalysis - Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
speech-to-text-websockets-python
pyechonest - Python client for the Echo Nest API
essentia - C++ library for audio and music analysis, description and synthesis, including Python bindings