Too large a graph to summarise here — watch the walkthrough: LTXDirector

SCAIL-2 — Character Animation

Take the motion out of one video and put your own character into it. The driving video's background is not kept — the scene is generated fresh around your character.

Fill these in

1. Load Video — your driving clip. Only the movement is used, never the appearance.

2. Load Image — the character to animate (person, mascot, drawing). One character only. The output video is sized to this image, so a portrait photo gives a portrait video.

3. Run SAM3 Video Track — upper node, fed by Load Video. Its text box names the subject to copy motion from. One person in the clip: leave human. Several people: pick one, e.g. man, woman in a red dress — otherwise SCAIL-2 gets two motion tracks and one character, and the result breaks.

4. Run SAM3 Video Track — lower node, fed by Load Image. Leave at human for a person. For a non-human character use its noun, e.g. dog, robot.

5. CLIP Text Encode (Positive Prompt) — describe your character and the action, e.g. a short-haired man in a striped shirt, hands on his hips, full body. Add full body if you want legs in frame.

6. Press Run.

Check the masks first

The two Preview Image nodes show the tracking masks. Exactly one subject should be coloured in each. If extra subjects light up, make the prompt in step 3 or 4 more specific, or raise detection_thres above 0.50. Do this before any long render — a bad mask wastes the whole run.

Length

Default is 81 frames at 16 fps — about 5 seconds, taken from the start of your clip.

To go longer, raise these two together and keep them equal: • Load Video → frame_load_cap • Wan SCAIL To Video → length

161 ≈ 10 s, 321 ≈ 20 s. SCAIL-2 is trained at 81 frames, so longer runs cost more VRAM and the character may drift.

To start somewhere other than the beginning, set Load Video → skip_first_frames (in frames, at 16 fps — 160 skips 10 s).

Sound

This workflow does not do sound. The render is always silent — SCAIL-2 generates picture only, and nothing in the graph carries audio through to the output.

Add the soundtrack afterwards in a video editor, using your original clip as the audio source. Trying to attach it here is not worth it: the render is a short slice of your clip, so the audio would not line up anyway.

Video format

The upload button accepts .mp4, .webm, .mkv and .gif. H.264 MP4 is the safe choice.

If a clip is rejected with "Invalid video file", re-encode it before uploading. A common cause is a movie-rip audio track (AC-3) that the pod's ffmpeg cannot decode:

ffmpeg -i input.mp4 -c:v libx264 -pix_fmt yuv420p -an clean.mp4

-an drops the audio, which this workflow does not use anyway. Keep the clip's own resolution — it is resized internally, so a huge 4K source only costs upload time.

Leave alone unless you know why • Negative Prompt — a fixed quality filter, not something to describe your video with. • KSampler — steps 6, cfg 1.0, euler / simple. These are tuned for the distilled LoRA; raising steps or cfg makes it worse, not better. • Create SCAIL-2 Colored Mask → replacement_mode — false here on purpose. Setting it true switches to the replacement behaviour (keeps the original background), which is what the scail2-replacement workflow already does. • Every model this workflow needs is already installed on the pod.

SCAIL-2 — Character Animation (two characters)

Same graph as the single-character animation, driven by a clip with two moving subjects. Only the inputs and the prompts differ.

There is only ONE Load Image — and that is correct

There is no second image node, and you should not add one. Both characters come from a single reference image that already contains both of them. SAM3 finds both figures inside that one picture and hands SCAIL-2 two separate coloured regions.

It has to be one real photograph of both subjects together — one background, one camera, one light. The output video is built from this frame, so whatever you hand over becomes the scene.

Do not glue two separate photos side by side. A collage keeps both backgrounds and the seam between them, and the render comes out looking like two videos in one frame. If all you have is a separate photo of each character, this workflow cannot merge them — run the single-character scail2-animation workflow on each one instead.

Fill these in

1. Load Image — one picture holding both characters. The output video is sized to this image, so a wide image gives a wide video. Both characters should be clearly separated and, if you want limbs animated, fully in frame.

2. Load Video — a driving clip with two moving subjects. Their motion is copied; their appearance is not.

3. Run SAM3 Video Track — upper node, fed by Load Video. Leave at human when the clip has exactly two people and you want both. Use a narrower word only if there are extra people to exclude.

4. Run SAM3 Video Track — lower node, fed by Load Image. Leave at human for two people. For non-human characters use a word that matches both, e.g. mascot or character — a word matching only one of them will leave the other untracked.

5. CLIP Text Encode (Positive Prompt) — describe both characters and what they do together, e.g. a black dog mascot character and a green-and-cream bird mascot character holding hands and dancing on a white stage.

6. Press Run.

Check the masks first — this matters most here

The two Preview Image nodes show the tracking masks. You need two differently coloured regions in each: two in the driving mask, two in the reference mask. If either shows one region, or three, fix the prompt in step 3 or 4 before rendering.

Who maps to whom is decided by Create SCAIL-2 Colored Mask → sort_by (area by default — biggest region first in both masks). If the wrong character gets the wrong motion, that pairing is the reason.

Length

Default is 81 frames at 16 fps — about 5 seconds, from the start of the clip.

To go longer, raise these together and keep them equal: • Load Video → frame_load_cap • Wan SCAIL To Video → length

161 ≈ 10 s, 321 ≈ 20 s. SCAIL-2 is trained at 81 frames — longer runs cost more VRAM and drift more, and two characters drift faster than one.

To start later in the clip, use Load Video → skip_first_frames (frames at 16 fps — 160 skips 10 s).

Sound

This workflow does not do sound. The render is always silent — SCAIL-2 generates picture only, and nothing in the graph carries audio through to the output.

Add the soundtrack afterwards in a video editor, using your original clip as the audio source. Trying to attach it here is not worth it: the render is a short slice of your clip, so the audio would not line up anyway.

Video format

The upload button accepts .mp4, .webm, .mkv and .gif. H.264 MP4 is the safe choice.

If a clip is rejected with "Invalid video file", re-encode it before uploading. A common cause is a movie-rip audio track (AC-3) that the pod's ffmpeg cannot decode:

ffmpeg -i input.mp4 -c:v libx264 -pix_fmt yuv420p -an clean.mp4

-an drops the audio, which this workflow does not use anyway. Keep the clip's own resolution — it is resized internally, so a huge 4K source only costs upload time.

Leave alone unless you know why • Negative Prompt — a fixed quality filter, not a place to describe your video. • KSampler — steps 6, cfg 1.0, euler / simple, tuned for the distilled LoRA. Raising steps or cfg makes it worse. • replacement_mode — false here on purpose; the background is meant to be generated fresh. To keep an original background instead, use the scail2-replacement workflow. • Every model this workflow needs is already installed on the pod.

SCAIL-2 — Character Replacement

Swap one person in your video for your own character. The original scene, background and everyone else stay exactly as they are.

Steps

1. Load Video — upload your clip. The output is sized to this video, not to your image.
2. Load Image — upload the character who takes their place. A clear, full-body photo works best.
3. Run SAM3 Video Track (the upper one, fed by Load Video) — its text box says who gets replaced. One person in the clip: leave human. Several people: name the one you want, e.g. man or woman in a red dress.
4. Run SAM3 Video Track (the lower one, fed by Load Image) — leave it at human.
5. Positive Prompt — describe your new character inside the video's setting, e.g. bearded man in a grey suit sitting at the desk.
6. Press Run.

Check the masks before a long render

The two Preview Image nodes show the tracking masks. In the driving mask, only the person being replaced should be coloured. If extra people light up, make the prompt in step 3 more specific, or raise detection_thres above 0.50.

Length

A default run is 81 frames at 16 fps — about 5 seconds, taken from the start of your clip.

For longer output raise these two together and keep them equal: • Load Video → frame_load_cap • Wan SCAIL To Video → length

161 ≈ 10 seconds, 321 ≈ 20 seconds. SCAIL-2 is trained at 81 frames, so longer runs cost more VRAM and the character may drift.

To start later in the clip, set Load Video → skip_first_frames (frames at 16 fps — 160 skips 10 s). Running the same clip in 81-frame slices at 0, 81, 162, 243 and joining the files is the alternative to one long render; expect a visible seam at each join.

Sound

This workflow does not do sound. The render is always silent — SCAIL-2 generates picture only, and nothing in the graph carries audio through to the output.

Add the soundtrack afterwards in a video editor, using your original clip as the audio source. Trying to attach it here is not worth it: the render is a short slice of your clip, so the audio would not line up anyway.

Video format

The upload button accepts .mp4, .webm, .mkv and .gif. H.264 MP4 is the safe choice.

If a clip is rejected with "Invalid video file", re-encode it before uploading. A common cause is a movie-rip audio track (AC-3) that the pod's ffmpeg cannot decode:

ffmpeg -i input.mp4 -c:v libx264 -pix_fmt yuv420p -an clean.mp4

-an drops the audio. Since this workflow keeps the original scene, re-encode from the highest-quality source you have — the output resolution is taken from this clip.

Leave alone unless you know why • Replace mode is already on — the toggles on Create SCAIL-2 Colored Mask and Wan SCAIL To Video are true. Turning them off gives the animation behaviour instead (original background discarded). • Negative Prompt — a fixed quality filter, not a place to describe your video. • KSampler — steps 6, cfg 1.0, euler / simple, tuned for the distilled LoRA. Raising steps or cfg makes results worse, not better. • Output size comes from the video via Get Image from Batch, not from your reference image — so a portrait clip stays portrait no matter what you upload. • Every model this workflow needs is already installed on the pod.

ControlNet (depth) — klein

1. Load Image depth (red) — drop the photo whose structure you want to copy. A depth map is auto-extracted (Depth Anything V2).
2. Load Image reference (red) — drop the subject/style reference to place into that structure.
3. Prompt — describe the result (default refcontrol).
4. RefControl strength (yellow) — the Lora node. Higher = follow the depth structure more strictly.
5. Press Run — result in Save Image.

Powered by the RefControl depth LoRA for klein 9B. The first depth run downloads the preprocessor weights (~1.3GB) once.

Face Swap — DarkBeast (klein 9B)

1. Target photo (red, top-left) — the picture whose face gets replaced. Ships with example.png so the graph runs out of the box.
2. Face to swap in (red, bottom-left) — the source face/identity to paste on.
3. Prompt — inside the Face Swap node; keep it simple, e.g. swap the face of the person with the reference face, keep pose, expression and lighting.
4. Steps = 5, CFG = 1 — DarkBeast is a distilled BFS model tuned for 5 steps / CFG 1. Do not raise them — higher values make it worse, not better.
5. Color Match (orange) regrades the result to the target's lighting so the swap blends in. Lower strength (or 0) to disable.
6. Press Run — the result is saved in Save Image.

DarkBeast Klein 9b V2 BFS — face-swap-specialized klein 9B (safetensors, loaded via UNETLoader).

Image Edit — klein (multi-reference)

1. Load Image (red, group image 1) — drop the reference picture. It ships with example.png so the graph runs out of the box.
2. Prompt — describe the edit inside the Image Edit node.
3. Reference images toggle — switch image 2 … image 10 on to use more reference pictures. Each toggle enables one Load Image group on the left.
4. Color Match (orange) — regrades the result to image 1's lighting/colors so edits blend in. Lower strength (or 0) to disable.
5. Press Run — the result is saved in Save Image.

FLUX.2 klein 9B (uncensored) — fast text → image + up to 10 reference images.

How to use

1. Prompt (orange) — type what you want to generate.
2. Two variants: Standard and Distilled (faster). Enable one and bypass the other with Ctrl-B.
3. Press Run — the result is saved in Save Image.

FLUX.2 klein 9B (uncensored) — fast text → image.

How to use

1. Prompt Builder (red) — type your prompt in the Description field (plain language is fine). For layout control, open the Ideogram 4 editor and drag boxes to place objects/text in regions.
2. Resolution Selector (orange) — choose aspect ratio / size.
3. Press Run — the image appears in Save Image.

"Image blocked by safety filter" comes from the model's own safety training, not ComfyUI.

How to use

1. Load Image — upload image 1 (required). Type the edit instruction in the Image Edit prompt field.
2. To combine pictures, enable Load Image 2 / 3 (right-click → Set Mode → Always) and upload.
3. Press Run — result in Save Image.

Predefined example — reset every GPU start; use Workflows → Save As to keep your own copy.

How to use

1. Load Image (red) — drop the photo whose camera angle you want to change.
2. Qwen Multiangle Camera (red) — drag the 3D handle to set the angle, or pick a preset. The prompt is built for you.
3. Press Run — the re-angled image appears in Save Image.

Powered by Qwen-Image-Edit-2511 + the multi-angle camera LoRA (4-step Lightning).

The quality of the style transfer depends largely on the quality of the RF inversion. These settings work well, but feel free to try other values.

How to use

1. Text to Image (red) — type your prompt in the text field, set width / height (and seed if you want).
2. Press Run — the image appears in Save Image.

Sizes: 1:1 1328×1328 · 16:9 1664×928 · 9:16 928×1664 · 4:3 1472×1104 · 3:4 1104×1472

Predefined example — reset on every GPU start. Use Workflows → Save As to keep your own copy.

Upscale to 4K

1. Load Image (red) — drop any image (e.g. one you made with the Text-to-Image workflow).
2. Target size (yellow) — Scale to Total Pixels sets the working resolution. 4 MP ≈ 4K; raise/lower for your GPU.
3. Refine (yellow) — the KSampler re-renders detail at the new size. denoise ~0.35–0.45: higher = more new detail, lower = closer to the original.
4. Press Run — the upscaled image lands in Save Image.

This is a single refine pass on an existing image. Generate first in the Text-to-Image workflow, then upscale here.

How to use

1. Load Image (red) — upload the image you want to edit.
2. Instruction — double-click the red Image Edit (Boogu) subgraph and type what to change in the prompt box.
3. Size (yellow) — output matches the input by default. Bypass Resize Image/Mask to keep the original size, or raise its megapixels (e.g. 4) for higher resolution — depends on your GPU.
4. Press Run — compare input vs result in Image Compare; the result is saved in Save Image.

Boogu Edit is instruction-based image editing with strong bilingual (English / 中文) text rendering.

How to use

1. Prompt — double-click the red Text to Image (Boogu Turbo) subgraph and type your description in the prompt box.
2. Resolution (yellow) — pick aspect ratio / size in Resolution Selector.
3. Press Run — the image appears in Save Image.

Boogu Turbo is a fast text-to-image model with strong bilingual (English / 中文) text rendering. For instruction-based image editing, open the Boogu Edit workflow.

How to use

1. Prompt — double-click the red Text to Image (Krea-2 Turbo) subgraph and type your description in Text String (User Prompt).
2. Resolution (orange) — pick aspect ratio / size in Resolution Selector.
3. Press Run — the image appears in Save Image.

Prompt enhancement is on by default; it expands your prompt using the model's own text encoder (no extra model needed). Toggle prompt_enhance inside the subgraph to turn it off.

Style LoRAs — set enable_lora? to true inside the subgraph, pick a krea2_* file in LoraLoaderModelOnly; the matching trigger word is added automatically. All 9 LoRAs are pre-installed.

Script → per-section SRT

1. Load audio (red, left) — upload the recording of your narration.
2. script (in the Align node) — paste your script; a blank line starts a new section. Each section becomes one SRT cue.
3. language — leave auto, or set ru / en / zh.
4. Press Run — WhisperX aligns your exact text to the speech and writes an SRT with one cue per section (exact start/end). A ⬇ Download SRT button appears when it finishes.

Sections whose words aren't found in the audio (e.g. a line you skipped while reading) are dropped and logged. Runs best on a GPU tier.

AUDIO -> SRT (transcribe, keep timing).

1. Upload your source audio to 'Load source audio'.
2. On 'Audio -> SRT' pick the spoken language (auto / en / ru / zh). ENGINE is whisperx — Whisper core + phoneme forced-alignment; the tightest word-level timing and the best accuracy of the two engines. The Qwen3-TTS bundle additionally offers 'qwen3-asr' as an alternative engine; every other voice bundle is WhisperX-only.
3. Run. The timestamped subtitles are saved to output/subs/transcript.srt and shown in the node.

Then translate that SRT text (keep the timestamps unchanged) and feed it to the 'SRT -> Audio' workflow to get a dubbed track with the SAME timing.

SRT -> dubbed AUDIO, voice cloned, original timing preserved (Fish Audio S2 Pro).

1. Paste your TRANSLATED subtitles into 'Fish S2 SRT Dub' (keep the same timestamps as the source SRT, only the text is translated).
2. Upload a clean 10-30s clip of the speaker to 'Reference voice'.
3. Run. The output language is detected from the SRT text itself.

Optional: press '🎙 Transcribe' on the dub node to preview the WhisperX transcription of your reference clip in 'ref_text' and fix it before Run. Left empty, the transcript is derived automatically.

Knobs: fit_to_timing (on = lock each line into its SRT slot), max_stretch (cap before audio sounds sped-up).

TTS + VOICE CLONE (Fish Audio S2 Pro, 80+ languages).

1. Upload a clean 10-30s clip of the target speaker to 'Reference voice'.
2. 'ref_text' — the exact words spoken in that clip. LEAVE EMPTY to have it transcribed automatically (WhisperX); type it manually for maximum accuracy.
3. Type the text to speak into 'text' — the language is detected from the text itself.
4. Run, listen in 'Save audio'.

Tip: leave 'Reference voice' unconnected to let the model pick a random voice.

The S2 server starts at boot; the first request after boot may wait a bit while it warms up.

Script → per-section SRT

1. Load audio (red, left) — upload the recording of your narration.
2. script (in the Align node) — paste your script; a blank line starts a new section. Each section becomes one SRT cue.
3. language — leave auto, or set ru / en / zh.
4. Press Run — WhisperX aligns your exact text to the speech and writes an SRT with one cue per section (exact start/end). A ⬇ Download SRT button appears when it finishes.

Sections whose words aren't found in the audio (e.g. a line you skipped while reading) are dropped and logged. Runs best on a GPU tier.

AUDIO -> SRT (transcribe, keep timing).

1. Upload your source audio to 'Load source audio'.
2. On 'Audio -> SRT' pick the spoken language (auto / en / ru / zh). ENGINE is whisperx — Whisper core + phoneme forced-alignment; the tightest word-level timing and the best accuracy of the two engines. The Qwen3-TTS bundle additionally offers 'qwen3-asr' as an alternative engine; every other voice bundle is WhisperX-only.
3. Run. The timestamped subtitles are saved to output/subs/transcript.srt and shown in the node.

Then translate that SRT text (keep the timestamps unchanged) and feed it to the 'SRT -> Audio' workflow to get a dubbed track with the SAME timing.

CHANGE VOICE (CosyVoice 3 native voice conversion) — keeps the words and the delivery, swaps only the timbre.

1. Upload the speech you want re-voiced (any length) to 'Source speech'. It is auto-split into <=25s chunks, re-voiced, and stitched back, so length is unlimited.
2. Upload a SHORT clean clip (3-30s) of the target speaker to 'Target voice'. Keep it SHORT (<=30s).
3. Run, listen in 'Save audio'.

This is REAL voice conversion — no transcription step, so pauses, emphasis and pacing survive intact.

To generate NEW speech from typed text instead, use the 'Voice Clone' workflow.

First run downloads the CosyVoice model (~GB) — give it a few minutes.

⚠️ Predefined example — it resets to the original every GPU start; edits here are lost. Save under a NEW name (Save As) to keep your own copy; custom workflows persist between sessions.

SRT -> dubbed AUDIO, voice cloned, original timing preserved.

1. Paste your TRANSLATED subtitles into 'CosyVoice SRT Dub' (keep the same timestamps as the source SRT, only the text is translated).
2. Upload a SHORT clean clip (3-15s, no music) of the speaker to 'Reference voice' — CosyVoice clones this timbre.
3. Pick language (auto works; en/zh are reliable).
4. Run. Each line is synthesized and time-stretched to fit its slot, so the output lines up with your video.

Knobs: fit_to_timing (on = lock to SRT timing), max_stretch (cap before audio sounds sped-up), speed.

Languages: EN and ZH are solid. Other officially supported languages can be less reliable in this model — prefer the Qwen3-TTS bundle for those.

First run downloads the CosyVoice model (~GB).

VOICE CLONE (CosyVoice 3 zero-shot).

1. Upload a SHORT clean clip (3-30s, no music) of the target speaker to 'Reference voice'. A reference clip is REQUIRED.
2. Type the text you want spoken into 'text' on the Voice Clone node.
3. Run, listen in 'Save audio'.

First run downloads the CosyVoice model (~GB) — give it a few minutes.

To re-voice EXISTING speech instead of generating new speech, use the 'Change Voice' workflow — it keeps the original words and delivery and only swaps the timbre.

⚠️ Predefined example — it resets to the original every GPU start; edits here are lost. Save under a NEW name (Save As) to keep your own copy; custom workflows persist between sessions.

Script → per-section SRT

1. Load audio (red, left) — upload the recording of your narration.
2. script (in the Align node) — paste your script; a blank line starts a new section. Each section becomes one SRT cue.
3. language — leave auto, or set ru / en / zh.
4. Press Run — WhisperX aligns your exact text to the speech and writes an SRT with one cue per section (exact start/end). A ⬇ Download SRT button appears when it finishes.

Sections whose words aren't found in the audio (e.g. a line you skipped while reading) are dropped and logged. Runs best on a GPU tier.

AUDIO -> SRT (transcribe, keep timing).

1. Upload your source audio to 'Load source audio'.
2. On 'Audio -> SRT' pick the spoken language (auto / en / ru / zh). ENGINE is whisperx — Whisper core + phoneme forced-alignment; the tightest word-level timing and the best accuracy of the two engines. The Qwen3-TTS bundle additionally offers 'qwen3-asr' as an alternative engine; every other voice bundle is WhisperX-only.
3. Run. The timestamped subtitles are saved to output/subs/transcript.srt and shown in the node.

Then translate that SRT text (keep the timestamps unchanged) and feed it to the 'SRT -> Audio' workflow to get a dubbed track with the SAME timing.

RE-DUB VOICE (Qwen3-TTS pipeline: transcribe -> re-speak, timing preserved).

This is NOT voice conversion. Qwen3-TTS has no native VC, so this workflow chains two steps: the source audio is transcribed with timestamps (Audio -> SRT), then every line is re-spoken from scratch by the cloned TARGET voice at its original timestamp (SRT Dub).

1. Upload the recording you want re-dubbed to 'Source audio'.
2. Upload a SHORT clean clip (3-15s, no music) of the TARGET voice to 'Target voice'. Leave 'ref_text' empty — it is transcribed automatically.
3. On the dub node pick the LANGUAGE of the source speech and run.

Line timing is preserved, but the words are re-generated, so intonation, pauses and emphasis inside each line are the model's, not the original speaker's. Two side effects worth knowing: a transcription error becomes a wrong word in the output, and any non-speech audio is dropped.

For REAL voice conversion — same words, same delivery, only the timbre swapped — use the CosyVoice 3 bundle (the change-voice pick) or Chatterbox Multilingual. Both do it natively with no transcription step.

SRT -> dubbed AUDIO, voice cloned, original timing preserved (Qwen3-TTS).

1. Paste your TRANSLATED subtitles into 'Qwen3-TTS SRT Dub' (keep the same timestamps as the source SRT, only the text is translated).
2. Upload a SHORT clean clip (3-15s, no music) of the speaker to 'Reference voice'.
3. 'ref_text' — the exact words spoken in that clip. LEAVE EMPTY to have it transcribed automatically (WhisperX); type it manually for maximum accuracy.
4. Pick the language of the TRANSLATED text and run.

Knobs: fit_to_timing (on = lock each line into its SRT slot), max_stretch (cap before audio sounds sped-up).

Each line is synthesized with the cloned voice and placed at its SRT timestamp, so the output lines up with your video.

VOICE CLONE (Qwen3-TTS 1.7B Base).

1. Upload a SHORT clean clip (3-15s, no music) of the target speaker to 'Reference voice'.
2. 'ref_text' — the exact words spoken in that clip. LEAVE EMPTY to have it transcribed automatically (WhisperX); type it manually for maximum accuracy.
3. Type the text you want spoken into 'text' and pick its language.
4. Run, listen in 'Save audio'.

First run loads the model (pre-baked at boot, a few seconds).

VOICE DESIGN (Qwen3-TTS 1.7B VoiceDesign).

No reference audio needed — describe the voice you want in plain language.

1. Type the text to speak into 'text'.
2. Describe the voice in 'instruct' (gender, age, mood, pace, accent — e.g. 'A raspy old pirate, slow and theatrical').
3. Pick the language and run.

Tip: to REUSE a designed voice, save its output and feed it into the Voice Clone workflow as the reference sample.

Script → per-section SRT

1. Load audio (red, left) — upload the recording of your narration.
2. script (in the Align node) — paste your script; a blank line starts a new section. Each section becomes one SRT cue.
3. language — leave auto, or set ru / en / zh.
4. Press Run — WhisperX aligns your exact text to the speech and writes an SRT with one cue per section (exact start/end). A ⬇ Download SRT button appears when it finishes.

Sections whose words aren't found in the audio (e.g. a line you skipped while reading) are dropped and logged. Runs best on a GPU tier.

AUDIO -> SRT (transcribe, keep timing).

1. Upload your source audio to 'Load source audio'.
2. On 'Audio -> SRT' pick the spoken language (auto / en / ru / zh). ENGINE is whisperx — Whisper core + phoneme forced-alignment; the tightest word-level timing and the best accuracy of the two engines. The Qwen3-TTS bundle additionally offers 'qwen3-asr' as an alternative engine; every other voice bundle is WhisperX-only.
3. Run. The timestamped subtitles are saved to output/subs/transcript.srt and shown in the node.

Then translate that SRT text (keep the timestamps unchanged) and feed it to the 'SRT -> Audio' workflow to get a dubbed track with the SAME timing.

VOICE CONVERSION (Chatterbox VC).

Replaces the VOICE in a recording while keeping the words, pacing and intonation of the original.

1. Upload the recording you want to convert to 'Source audio'.
2. Upload a SHORT clean clip (3-15s, no music) of the TARGET voice to 'Target voice'.
3. Run, listen in 'Save audio'.

First run loads the VC model (pre-baked at boot, a few seconds).

SRT -> dubbed AUDIO, voice cloned, original timing preserved (Chatterbox Multilingual v3).

1. Paste your TRANSLATED subtitles into 'Chatterbox SRT Dub' (keep the same timestamps as the source SRT, only the text is translated).
2. Upload a SHORT clean clip (3-15s, no music) of the speaker to 'Reference voice'. No transcript needed.
3. Pick the language code of the TRANSLATED text (en / ru / zh / ...) and run.

Knobs: fit_to_timing (on = lock each line into its SRT slot), max_stretch (cap before audio sounds sped-up).

Each line is synthesized with the cloned voice and placed at its SRT timestamp, so the output lines up with your video.

TTS + VOICE CLONE (Chatterbox Multilingual v3, 23 languages).

1. Upload a SHORT clean clip (3-15s, no music) of the target speaker to 'Reference voice'. No transcript needed.
2. Type the text to speak into 'text' and pick its language code (en / ru / zh / ...).
3. Run, listen in 'Save audio'.

Tip: leave 'Reference voice' unconnected to use the model's default voice.

First run loads the model (pre-baked at boot, a few seconds).