A script lives or dies on the table read. If two characters sound like the same person, the scene flatlines. ChatGPT averages across its training data, so every character lands in the same rhythm, the same vocabulary register, the same sentence length. Action lines arrive in identical sluglines: INT. COFFEE SHOP, DAY. She smiles warmly. The room falls silent. TextSight rewrites for spoken voice and gives each character room to be distinct, across feature screenplays, TV episodes, short films, web series, YouTube long-form, and video ads. Honest framing: spoken voice plus character distinctiveness, fully disclosed under the WGA AI policy.
A script needs a king who talks like a king and a courtier who does not. ChatGPT writes both like the average article on screenwriting. The result reads like a single narrator wearing different name tags.
Large language models are trained to produce the most likely next token. The most likely token, averaged over all dialogue ever written, is grammatical, mid-register, and rhythmically smooth. That is the voice of nobody in particular. Drama lives in specificity. Every working script puts characters into rhythmic and lexical opposition on purpose so the audience can tell them apart by ear.
The teen sounds like the parent. The detective sounds like the suspect. Every line lands in the 12 to 18 word band. Real scripts spread that range hard: one character speaks in clipped four-word lines, another runs 25-word run-ons, a third uses fragments. Sentence length is the cheapest character marker on the page.
ChatGPT picks mid-register words for all dialogue. Nobody is allowed to be crude, nobody is allowed to be ornate, everyone lands in neutral English. Real characters live at the edges. A working dialogue pass lets one character curse, one over-formalise, one use a single trade jargon nobody else knows.
Real people interrupt themselves, trail off, restart, contradict the last clause, talk over each other. AI characters finish every sentence. The cleanness is a fingerprint by page three. One self-interruption per character per scene closes most of the gap.
Invisible when you read a draft alone. Obvious the moment actors are in the room. Catch them before the read, not after.
Every character speaks in the same rhythm. Sentences land in the same length band, contractions appear at the same rate, asides happen at the same frequency. Two characters in a scene are now interchangeable on the page. The director circles every line and asks who is who. The fix is character cards plus a line-by-line rhythm pass.
She smiles warmly. He nods thoughtfully. The room falls silent. Tension fills the air. AI defaults to these because they parsed every screenwriting textbook ever published. Cut every one. Replace with a single specific gesture: she taps the rim of the cup twice. He looks at the door, looks back, looks at the door again. Specific beats are character beats.
INT. COFFEE SHOP, DAY. INT. OFFICE, DAY. EXT. STREET, NIGHT. Every cafe scene gets the same slug, every workplace scene gets the same slug, every outdoor scene gets the same slug. Real scripts vary: INT. THE DINER MARTA'S GRANDFATHER OPENED, 2:14 PM. The slug carries information. AI slugs carry none.
She smiles warmly, he speaks quietly, they look sadly. Adverbs in action lines are the script equivalent of telling instead of showing. Drop every one and replace with an action that produces the emotion: she does not smile, she presses her thumb into her palm. The actor performs the emotion, the writer stages the moment.
AI characters speak in finished sentences. Real characters do not. Real scripts use fragments, false starts, three-word lines, mid-clause cut-offs (marked with --), trails (marked with ...). One mid-line interruption per page is the minimum for any working dialogue scene with two speakers in conflict.
Characters in AI scripts announce why they are doing what they are doing. I am angry because... I am leaving because... I cannot stay because... Real characters act and let the audience figure out the motive. Cut every "because" clause in dialogue and rewrite the scene so the action carries the meaning. This is the single highest-leverage edit on any AI-drafted script.
Every block of text that ends up performed or spoken sits inside the same workflow. The mode and the depth of the character pass change with the format.
The longest character-voice job. Six to twelve speaking parts, each one needs a voice card and a line-by-line pass. Run dialogue scenes in Light, action paragraphs in Balanced. Plan on 20 minutes per scene from raw ChatGPT to table-read-ready. A full feature is several weeks of disciplined nightly work, not a weekend.
Tighter than features because the showrunner's voice already exists across earlier episodes. Use prior shooting drafts as voice references and ask the AI rewriter to match the cadence. Light for dialogue, Balanced for stage directions. Network notes hit the dialogue first, so the character pass is the highest leverage edit.
Two or three speaking parts, every line is load-bearing. Run the whole script through Balanced for the prose pass, then do a Light pass on each character's dialogue separately so the rewrite never bleeds vocabulary between characters. Festival shorts are read by gatekeepers who scan a hundred drafts a week; AI-flavoured dialogue gets cut in the first three pages.
Looser registers than network TV but the same character-voice rules. Plus the on-platform analytics layer: YouTube and TikTok shorts series live on first-30-second retention, so the cold open is the deciding shot. Run the cold open through Balanced and then read every line aloud at recording pace before the shoot.
Single-speaker scripts where character distinctiveness matters less than spoken cadence and host voice. Closest to the podcast authenticity workflow. Run the whole script through Balanced, then read each paragraph aloud. The opener gets rewritten from scratch most of the time because ChatGPT defaults to "welcome to today's video" openers that lose 8 to 12 percent of viewers in fifteen seconds.
The shortest format and the most sensitive because brand-supplied copy locks the wording. Light mode only. Rewrite for spoken delivery without changing approved claims. The voice actor reads the rewritten version on set. Stage directions stay in the brief, not in the rewritten block.
Free fits a short film or a single feature scene. Pro fits a working screenwriter rewriting nightly across multiple projects. Business fits writers' rooms and production houses. Full details on the pricing page.
Billed $89.88/year — Save $30
Billed $179.88/year — Save $60
Billed $359.88/year — Save $120
Yearly billing saves 25%. View full pricing →
Scripts are the one format where Maximum is not the right default. The averaging that helps prose flattens character voice further. The mode map below is built for the page, not for the article.
Smallest edits, preserves character intent, leaves rhythm choices alone. The right setting for any line that has to come out of a specific character's mouth. Run dialogue blocks separately from action paragraphs and stay in Light. Vocabulary register stays where you put it, contractions stay where you intended them.
The default for action paragraphs, scene-setting prose, and anything that is not character dialogue. Restores varied sentence rhythm, cuts the generic gestures, and breaks the slugline template. Safe on action lines because there is no character voice to protect, the writer's voice is allowed to come through.
Aggressive rewrite that averages across the whole document. Helpful on treatments, outlines, beat sheets, and pitch documents where the prose is selling the story rather than performing it. Risky on actual script pages because it can flatten character voice further. Never run a dialogue scene through Maximum unmonitored. Use it on the treatment, not the screenplay.
Twenty minutes per scene from raw ChatGPT to table-read-ready. The AI rewriter handles cadence and the generic-isms. The writer handles character voice.
Let ChatGPT produce the rough scene. Do not fix AI prose in the draft stage. Keep the structure, the beats, the scene shape. Throw the wording away. The AI rewriter is the right place to fix wording, not the prompt.
Copy the scene out of Final Draft or WriterDuet as plain text. Separate every CHARACTER NAME plus dialogue speech from the surrounding action paragraphs. The two go through different modes. Mixing them in one paste loses control of the rewrite depth.
Paste the action paragraphs into app.textsight.ai and run Balanced. Watch for generic gestures (she smiles warmly), templated sluglines, and emotion adverbs. Accept the rewrite suggestions on the highlighted spans. Paste the cleaned block back into the script.
Run each character's lines separately. Light mode preserves their intent. Then do a one-pass character card check: does the line match the vocabulary range, sentence length tendency, and contraction habit you defined for this character? Adjust by hand for anything that does not match.
Read every line at delivery speed. Mark every spot you stumbled or that did not sound like the character. Fix by hand. Then run the scene with actors. If any two characters still sound interchangeable when you close your eyes, the dialogue is still averaged. Send the marked-up scene back into Light for one more pass and adjust the character cards.
Opening of a confrontation scene from a feature about a fired detective and the rookie partner who turned her in. First as ChatGPT drafted it, then the rewritten rewrite that survived the table read. Same beats, two now-distinct voices.
INT. COFFEE SHOP, DAY Marta sits at the corner table. Daniel approaches and sits down across from her. He smiles warmly. DANIEL I am glad you agreed to meet with me today. I know this is difficult for you. MARTA I am here because I want to understand why you did what you did. I am not here to forgive you. DANIEL I understand. I want to explain everything that happened. I think it is important that you hear the full story.
INT. PALERMO'S, 7:42 AM Marta. Corner table. Cold coffee. She is reading the same page she was reading twenty minutes ago. Daniel slides into the chair across from her. Does not sit. Hovers. MARTA You're late. DANIEL Traffic. MARTA You walked. A beat. Daniel sits. DANIEL I wanted -- MARTA No.
What changed: slug rebuilt with a specific location and exact time (Palermo's, 7:42 AM). Action lines cut from "He smiles warmly" to specific gestures (Hovers. Does not sit). Marta gets clipped two-word lines that catch Daniel's lie (You walked). Daniel gets the half-sentence interrupt (I wanted --). The "because" motivation announcement is gone. Two characters now sound like two different people. Score moved 67 points.
Sister guide for solo, interview, narrative, and sponsor-read podcast scripts.
For podcast scripts →Long-form video scripts and Shorts hooks. First-30-second retention focus.
For YouTube scripts →The 0-100 score explained, with target bands for screen, spoken, and written formats.
Read the explainer →The standalone AI rewriter tool. Three modes, sentence-level highlights, voice-preserving rewrites.
Open the AI rewriter →Free to try. No card. Rewrite a scene, give each character a distinct voice, and walk into the read with a draft that does not sound like one narrator wearing different name tags. Your first scan in about six seconds.