StemRoller vs Spleeter

Struggling to choose between StemRoller and Spleeter? Both products offer unique advantages, making it a tough decision.

StemRoller is a Audio & Music solution with tags like stem-extraction, vocal-isolation, instrumental-isolation, ai, deep-learning.

It boasts features such as Isolates and extracts vocal and instrumental stems from stereo audio files, Uses advanced AI and deep learning for audio source separation, Allows editing and processing of isolated stems, Supports common audio formats like MP3, WAV, FLAC, etc., Available as VST/AU plugin or standalone application and pros including Powerful stem separation and extraction, Intuitive and easy to use interface, Saves time compared to manual stem creation, Great for remixing, sampling, karaoke tracks, Impressive quality and accuracy.

On the other hand, Spleeter is a Audio & Music product tagged with audio-separation, remixing, music-manipulation, deep-learning.

Its standout features include Uses deep learning models for audio source separation, Separates audio into stems of vocals, drums, bass, piano and other instruments, Provides pre-trained models for 2, 4 and 5 stem separation, Command line interface and Python library for integration into apps, Open source under MIT license, and it shines with pros like High quality separation powered by deep learning, Pre-trained models require no setup or training, Modular design allows customizing for new separation tasks, Actively maintained by research team at Deezer.

Feature	StemRoller	Spleeter
Overall Score	N/A	N/A
Primary Category	Audio & Music	Audio & Music

Product Overview

StemRoller

Description: StemRoller is an audio editing tool that allows for the isolation and extraction of vocal and instrumental stems from stereo audio files. It utilizes advanced artificial intelligence and deep learning techniques to break down tracks into separate vocal and instrumental components.

Spleeter

Description: Spleeter is an open-source audio source separation tool intended for music manipulation. It separates audio recordings into stems of vocals, drums, bass, and other instruments for remixing or analysis. It utilizes deep learning for high quality source separation.

Key Features Comparison

StemRoller Features

• Isolates and extracts vocal and instrumental stems from stereo audio files
• Uses advanced AI and deep learning for audio source separation
• Allows editing and processing of isolated stems
• Supports common audio formats like MP3, WAV, FLAC, etc.
• Available as VST/AU plugin or standalone application

Spleeter Features

• Uses deep learning models for audio source separation
• Separates audio into stems of vocals, drums, bass, piano and other instruments
• Provides pre-trained models for 2, 4 and 5 stem separation
• Command line interface and Python library for integration into apps
• Open source under MIT license

Pros & Cons Analysis

StemRoller

Pros

• Powerful stem separation and extraction
• Intuitive and easy to use interface
• Saves time compared to manual stem creation
• Great for remixing, sampling, karaoke tracks
• Impressive quality and accuracy

Cons

• Requires powerful computer for real-time processing
• Limited to stereo audio input
• Not free - subscription or one-time purchase required
• Some artifacts may be present in separated stems

Spleeter

Pros

• High quality separation powered by deep learning
• Pre-trained models require no setup or training
• Modular design allows customizing for new separation tasks
• Actively maintained by research team at Deezer

Cons

• Pre-trained models work best on pop/rock music
• Requires powerful GPU for real-time separation
• Limited documentation and examples

Pricing Comparison

StemRoller

• Subscription
• One-time Purchase

Spleeter

• Open Source