Take your headphone sound to the next level with Wavelet
Wavelet is a powerful system-wide audio equalizer designed for Android users who want their headphones to perform at their absolute best.
First-class AutoEq integration
Wavelet pioneered AutoEq on Android. It allows you to instantly enhance your headphones with one of the 5000+ AutoEq profiles based on the Harman target curve the industry standard for achieving neutral high-fidelity sound.
Have your own data? Easily import custom optimizations from autoeq.app or squig.link. Whatever headphone you use this app helps it sound its absolute best.
Smart & adaptive
Wavelet adapts in real time to your audio setup:
· Headphone-specific features automatically appear when wired Bluetooth USB headphones or DACs are connected
· ISO 226-based equal loudness compensation adjusts based on your listening volume
· Your saved profile automatically loads when switching between different headphones
System-wide compatibility
Wavelet enhances sound across many audio sources not just a single app. Enjoy consistent optimized audio no matter where you’re listening. From your favorite streaming services to offline media players.
Feel the subwoofer rumble
Wavelet's custom bass tuner doesn't just boost bass. It mimics the feel of a subwoofer making your headphones sound more immersive and dynamic.
Packed with audiophile features
· Limiter with automatic preamp adjustment to prevent clipping
· Graphic equalizer for manual fine-tuning
· Channel balance for asymmetric volume compensation
· Virtualizer for a spacious soundstage
· Reverberation for room simulation
Experience the power of adaptive high-fidelity audio with Wavelet. No root required.
Wavelet is a powerful system-wide audio equalizer designed for Android users who want their headphones to perform at their absolute best.
First-class AutoEq integration
Wavelet pioneered AutoEq on Android. It allows you to instantly enhance your headphones with one of the 5000+ AutoEq profiles based on the Harman target curve the industry standard for achieving neutral high-fidelity sound.
Have your own data? Easily import custom optimizations from autoeq.app or squig.link. Whatever headphone you use this app helps it sound its absolute best.
Smart & adaptive
Wavelet adapts in real time to your audio setup:
· Headphone-specific features automatically appear when wired Bluetooth USB headphones or DACs are connected
· ISO 226-based equal loudness compensation adjusts based on your listening volume
· Your saved profile automatically loads when switching between different headphones
System-wide compatibility
Wavelet enhances sound across many audio sources not just a single app. Enjoy consistent optimized audio no matter where you’re listening. From your favorite streaming services to offline media players.
Feel the subwoofer rumble
Wavelet's custom bass tuner doesn't just boost bass. It mimics the feel of a subwoofer making your headphones sound more immersive and dynamic.
Packed with audiophile features
· Limiter with automatic preamp adjustment to prevent clipping
· Graphic equalizer for manual fine-tuning
· Channel balance for asymmetric volume compensation
· Virtualizer for a spacious soundstage
· Reverberation for room simulation
Experience the power of adaptive high-fidelity audio with Wavelet. No root required.
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Wavelet: headphone equalizer / What's New in vUnknown
- Update AutoEq database
- Update UI with Material Expressive elements
- Expand enhanced session detection capabilities
- Replace AIDL mode with automatic AIDL detection. Not al features are available in this mode: https://pittvandewitt.github.io/Wavelet/Troubleshooting/#some-feature-is-missing
If you wish to help translate Wavelet into your language, please visit https://github.com/Pittvandewitt/Wavelet-strings
- Update UI with Material Expressive elements
- Expand enhanced session detection capabilities
- Replace AIDL mode with automatic AIDL detection. Not al features are available in this mode: https://pittvandewitt.github.io/Wavelet/Troubleshooting/#some-feature-is-missing
If you wish to help translate Wavelet into your language, please visit https://github.com/Pittvandewitt/Wavelet-strings
