kapre
Keras Audio Preprocessors for deep learning audio tasks.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is kapre?
Kapre is a library that provides Keras layers for preprocessing audio data. It simplifies the process of integrating audio signal processing into neural network models, making it easier to work with audio in machine learning projects.
Key differentiator
“Kapre stands out as a specialized library for Keras and TensorFlow, offering unique audio preprocessing capabilities directly within neural network models.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
Kapre primarily supports basic transformations like STFT and Mel-spectrogram, lacking more sophisticated features such as deep learning-based denoising or source separation.
Integration is tightly coupled with Keras layers and models, making it difficult to use Kapre with TensorFlow's functional API or PyTorch without significant effort.
The library has a relatively small user base and the official documentation is sparse, leading to fewer resources for troubleshooting and learning best practices.
Fit analysis
Who is it for?
✓ Best for
Developers working on audio preprocessing in Keras/TensorFlow projects.
Data scientists needing to integrate complex audio transformations into their models.
✕ Not a fit for
Projects requiring real-time audio processing outside of a deep learning context.
Applications that do not require or benefit from the specific audio preprocessing layers provided by kapre.
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with kapre
Step-by-step setup guide with code examples and common gotchas.