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Spleeter VS Easy ML for Java

Compare Spleeter VS Easy ML for Java and see what are their differences

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Spleeter logo Spleeter

Isolate vocals from any song using AI by Deezer

Easy ML for Java logo Easy ML for Java

The easiest way to start with Machine Learning in Java
  • Spleeter Landing page
    Landing page //
    2023-10-21
Not present

Spleeter features and specs

  • High Performance
    Spleeter utilizes deep learning technologies to achieve high-quality separation of vocals and other musical elements, making it a powerful tool for audio processing tasks.
  • Open Source
    Being an open-source project, Spleeter is freely accessible and can be modified and improved by the community, fostering innovation and collaboration.
  • Ease of Use
    With pre-trained models and straightforward API, Spleeter is user-friendly, allowing users to quickly start separating audio without needing extensive background in machine learning.
  • Speed
    Spleeter is optimized for fast processing, enabling quick separation of tracks even on standard hardware, which is beneficial for users needing rapid results.
  • Community and Documentation
    The project has an active community and comprehensive documentation, offering support and resources to help users resolve issues and maximise the tool’s potential.

Possible disadvantages of Spleeter

  • Resource Intensive
    Deep learning models require significant computational power, which means Spleeter can be demanding on system resources, especially for higher quality separations.
  • Quality Limitations
    Although it performs well, Spleeter might not always achieve perfect separation, and certain complex mixes may still present challenges, resulting in artifacts or quality loss.
  • File Size
    The pre-trained models and resulting files can be large, potentially requiring substantial storage space, which could be an issue for users with limited disk space.
  • Dependency Management
    Setting up Spleeter and ensuring all dependencies are correctly installed can be cumbersome, particularly for less technically-oriented users unfamiliar with Python environments.
  • Use Case Limitations
    Spleeter is specifically designed for source separation, meaning its utility is somewhat limited to this function and may not be suitable for users looking for a broader range of audio processing features.

Easy ML for Java features and specs

No features have been listed yet.

Analysis of Spleeter

Overall verdict

  • Spleeter is generally considered a good tool for those needing to separate audio tracks into stems. Its ease of use, effectiveness, and free availability make it popular among musicians, producers, and audio engineers.

Why this product is good

  • Spleeter is an open-source music separation tool developed by Deezer that allows users to separate audio tracks into individual components like vocals and instruments. It is praised for its high separation quality and speed, leveraging deep learning techniques. The tool is user-friendly and can be easily accessed via a command-line interface or integrated into various audio processing workflows.

Recommended for

    Musicians, audio engineers, producers, and sound designers who require efficient audio separation for remixes, practice, or analysis purposes.

Analysis of Easy ML for Java

Overall verdict

  • Easy ML for Java appears to be a lightweight, approachable library aimed at bringing machine learning capabilities to Java developers without requiring deep ML expertise or switching to Python-centric ecosystems. It seems suitable for developers who want to integrate basic ML functionality into existing Java applications with minimal overhead, though it likely lacks the depth, community support, and cutting-edge features of major frameworks like TensorFlow, PyTorch, or scikit-learn.

Why this product is good

  • Native Java implementation avoids the need for language interop or JNI bridges to Python-based ML libraries
  • Simpler API design makes it more accessible for Java developers without extensive ML background
  • Documentation via GitBook suggests an organized, readable learning path for newcomers
  • Lightweight footprint can be beneficial for integrating into existing Java-based systems without heavy dependencies
  • Good fit for educational purposes or prototyping simple ML concepts within a Java codebase

Recommended for

  • Java developers who want to experiment with ML without learning Python
  • Small to medium projects requiring basic classification, regression, or clustering functionality
  • Students or educators teaching foundational ML concepts using Java
  • Teams with existing Java infrastructure who need lightweight ML integration without major architectural changes
  • Prototyping and proof-of-concept work rather than production-grade, large-scale ML systems

Spleeter videos

+ Add

SPLEETER VS IZOTOPE RX7 (Which is the best DIY acapella tool?)

More videos:

  • Review - How-to Spleeter — Split audio with Deezer's AI tool in 2019
  • Tutorial - How to Get the Stems of ANY Song || Installing & Using Spleeter
  • Demo - Sober
  • Demo - Wadani
  • Demo - pl

Easy ML for Java videos

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Category Popularity

0-100% (relative to Spleeter and Easy ML for Java)

Spleeter

Easy ML for Java

Music
100 100%
Music
0% 0
Artifical Intelligence
0 0%
Artifical Intelligence
100% 100
Audio & Music
100 100%
Audio & Music
0% 0
Machine Learning
0 0%
Machine Learning
100% 100

User comments

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Social recommendations and mentions

Based on our record, Spleeter seems to be more popular. It has been mentiond 135 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Spleeter mentions (135)

  • When One Track Becomes Four: How AI Stem Splitting Gave Me Back My Creative Time
    The category of tools leveraging AI for stem separation works best when you treat them like a utility, not a creative oracle. They are sophisticated pattern recognition systems, not mind-readers. I learned this the hard way. On one test, I tried splitting a heavily distorted guitar track layered with synths. The result sounded watery and thin. That wasn’t the tool failing—it was me expecting too much from a... - Source: dev.to / 8 months ago
  • Guitar chord karaoke with Vamp, Chordino, and FFmpeg
    Either creating stems from karaoke multitracks (e.g. [0]) or using Spleeter [1] 5-stem mode, probably [0] https://www.karaoke-version.com/ [1] https://github.com/deezer/spleeter. - Source: Hacker News / over 1 year ago
  • Synchronizing pong to music with constrained optimization
    Absolutely wonderful! > "We obtain these times from MIDI files, though in the future I’d like to explore more automated ways of extracting them from audio." Same here. In case it helps: I suspect a suitable option is (python libs) Spleeter (https://github.com/deezer/spleeter) for beat times. I haven't ventured into this yet though so I may be off. My ultimate goal is to be able to do it 'on the fly', i.e. In a... - Source: Hacker News / about 2 years ago
  • Are stems a good way of making mashups
    Virtual dj and others stem separator is shrinked model of this https://github.com/deezer/spleeter you will get better results downloading original + their large model. Source: over 2 years ago
  • Big News!
    I have used multiple tools at this point. It depends on the scene. I use https://ultimatevocalremover.com/, https://github.com/deezer/spleeter/, iZotope RX. There are also multiple options online, I would personally recommend https://vocalremover.org/. Source: almost 3 years ago
View more

Easy ML for Java mentions (0)

We have not tracked any mentions of Easy ML for Java yet. Tracking of Easy ML for Java recommendations started around Jan 2023.

What are some alternatives?

When comparing Spleeter and Easy ML for Java, you can also consider the following products

LALAL.AI - The #1 vocal remover, now a full audio toolkit — separate stems, clean up voice recordings, change and clone voices, all in one place.

Moises - Separate audio tracks using state-of-the-art AI algorithm

VocalRemover.org - Vocal Remover and Isolation. Separate voice from music out of a song free with powerful AI algorithms

Splitter.ai - Isolating instruments from music is now possible using AI, and Splitter is based on Deezer's open source research project Spleeter to accomplish this.

PhonicMind - Make karaoke out of any song with AI powered vocal remover

Acapella Extractor - Isolate vocals from any song for free

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