InfiniteTalk AI - Audio-Driven Video

Introduction to InfiniteTalk AI

InfiniteTalk AI is an audio‑driven video generation platform that converts a single image or an existing video plus audio into lifelike talking videos. It uses sparse‑frame video dubbing to deliver accurate lip synchronization, expressive head and body motion, and consistent visual identity over extended durations.

The platform is designed for creators working with long‑form audio—such as podcasts, lectures, training content, and narration—as well as teams that need efficient dubbing and localization. It supports single‑person and multi‑person scenarios, enabling complex dialogue and multi‑character sequences with individual audio control.

Key Takeaways

• Audio‑driven talking video from image‑to‑video or video‑to‑video inputs
• Sparse‑frame video dubbing with accurate lip sync and full‑body motion
• Unlimited‑length generation with consistent identity preservation
• Multi‑person video support with separate audio tracks and reference masks
• Batch processing for scaled workflows and long‑form content
• Current output resolutions: 480p and 720p (higher resolutions planned)
• Broad I/O support: audio (MP3, WAV, M4A), images (JPG, PNG, WebP), videos (MP4, MOV, AVI), and transcripts (TXT, SRT)
• Outputs include MP4 (H.264/H.265), WebM (VP9), and frame sequences (PNG/JPG)

How InfiniteTalk AI Works

Users start by selecting a source: either a single image or an existing video. They then upload the corresponding audio—speech, podcast, or dialogue—and can optionally provide transcripts. For multi‑person scenes, separate audio tracks and reference masks can be supplied to control each character’s alignment and timing.

The system applies sparse‑frame video dubbing to drive lip shapes, facial expressions, head movement, and body posture from the audio while maintaining the subject’s identity, lighting, and background. For video‑to‑video workflows, the platform preserves source framing and motion cues where appropriate. The result is a generated talking video that aligns closely with the audio track.

Exports are available in MP4 or WebM, as well as frame sequences for post‑production pipelines. Current resolution options include 480p and 720p, with higher resolutions planned. The pipeline supports long‑form and batch processing to handle extended content.

Core Benefits and Applications

• Long‑form content conversion: Turn podcasts, lectures, and narrated training modules into corresponding talking videos without manual keyframing or short‑clip limitations.
• Dubbing and localization: Maintain a consistent visual identity across languages while aligning lip movements and body expressions to new audio tracks.
• Multi‑character productions: Produce dialogues, interviews, and panel discussions by assigning individual audio tracks and masks to each participant.
• Content repurposing: Generate talking avatar versions of existing audio archives for social channels, knowledge bases, and courseware.
• Scalable workflows: Use batch processing and frame sequence exports for streamlined post‑production and integration with existing editing pipelines.

Pricing and Credits (One‑Time)