Voice Crush

Available on both iOS and Android, the platform uses deep learning models trained specifically on human speech patterns to distinguish between the voice signal and unwanted audio artifacts, enabling precise removal without affecting the clarity or natural quality of the retained speech.

AI denoising is the foundational capability: Voice Crush's deep learning noise reduction separates human voices from background noiseair conditioning, keyboard clicks, traffic, crowd chatter, and other environmental soundsproducing a clean audio track from a recording made in imperfect acoustic conditions.

This noise separation capability makes it practical to record podcasts, video narration, video calls, and voice memos in ordinary environments rather than requiring a professional recording studio.

The stutter and anti-stuttering feature identifies moments of speech disfluency in recordings and removes or smooths them, making spoken content sound more fluent and confident than the original recording.

This is particularly valuable for speakers who experience natural disfluency that they want to edit out of published content, or for recordings where nervousness or speaking pace created awkward repetitions that distract from the substance of what was said.

Filler word removal automatically detects and eliminates common speech fillersum, uh, ah, like, you knowacross recordings in multiple languages.

Similarly, the mouth sounds remover targets the lip smacks, saliva sounds, and other mouth noises that microphones pick up at close range and that are distracting in professional audio.