SpeakerSplit is an AI-powered tool designed to simplify the process of video and audio editing. It enables users to transcribe audio, separate speakers into individual tracks, add captions, remove silence and filler words, and even extract vocals from songs. By leveraging advanced artificial intelligence, SpeakerSplit eliminates the need for complex software or manual timeline scrubbing, making it accessible and efficient for content creators, podcasters, and professionals.
With support for a wide range of file formats including MP4, WebM, MOV, and AVI, SpeakerSplit automatically extracts audio for processing. The platform supports over 20 languages and provides accurate speaker separation and transcription, allowing users to focus on their creative work rather than tedious editing tasks.
SpeakerSplit operates through a simple four-step process:
Upload Audio or Video File: Users can upload their audio or video file via drag-and-drop or by clicking the upload button. The system supports multiple video formats and automatically extracts the audio for processing.
Transcribe and Separate Vocals: Once uploaded, the AI processes the file, transcribing the audio into text and separating each speaker into individual tracks. A built-in editor allows users to refine the transcript and speaker labels before exporting.
Download Your Files: After processing, users can review and edit the transcript if needed. They can then download the results in various formats, including isolated vocal tracks in WAV or MP3 format.
Export in Your Format: Finally, users can choose the desired output format for both the transcript and the audio files, ensuring compatibility with their workflow.
SpeakerSplit offers significant time and cost savings by automating tasks that would otherwise require extensive manual editing. It is ideal for podcasters, content creators, and professionals who need to manage large volumes of audio and video content efficiently. Its AI-driven accuracy ensures high-quality results, making it a valuable tool for anyone looking to streamline their audio processing workflow.
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