tts

Overview of tts skill

What the tts skill does

The tts skill turns text into speech audio for voice generation, narration, dubbing, and timeline-aligned playback. It is best for users who need a working audio file, not just a chat response: generate a voice clip from a prompt, convert an article or text file into speech, or render SRT-driven narration with timing control.

When to install tts

Install the tts skill if your workflow includes tts install-style setup, recurring text-to-speech jobs, or you need a repeatable tts usage path instead of improvising prompts each time. It is especially useful when you want one skill to handle both quick “speak this” jobs and more structured voice generation from subtitles or segmented text.

What makes it different

This tts skill is built around real execution paths: a default simple mode, a timeline mode, and backend-aware scripts. That matters if you care about output format, voice cloning, subtitle timing, or choosing between local and cloud TTS. It is less useful if you only want a one-off natural-language prompt with no file output or no control over the rendering pipeline.

How to Use tts skill

Install and locate the entrypoints

Use the repo-provided install flow first: npx skills add NoizAI/skills --skill tts. Then read skills/tts/SKILL.md, followed by scripts/tts.py, scripts/render_timeline.py, and scripts/text_to_srt.py. Those files tell you the real command shape, supported modes, and what input each mode expects.

Turn a rough request into a usable prompt

For best tts usage, be explicit about four things: the text source, the voice goal, the output format, and whether timing matters. Good inputs look like: “Convert this article to MP3 using a calm English voice,” “Render these SRT subtitles into timeline-accurate audio,” or “Generate an OPUS voice note from this script using the reference audio.” Weak inputs like “make it sound better” force guesswork and usually produce mismatched pacing or format.

Choose the right workflow

Use simple mode when you have plain text or a text file and need a single audio file quickly. Use timeline mode when the text is already segmented, when you need subtitles to line up, or when each segment may need different voice settings. If you only want speech output, stay in the smallest path; if you need per-segment control, start with SRT or create one from text first.

Read the files that change output quality

The most useful files are scripts/tts.py for the command interface, scripts/noiz_tts.py for cloud-backed options, and scripts/render_timeline.py for alignment rules. Check scripts/test_tts.py if you want to understand edge cases around inputs and defaults. Also review ref_3rd_party.md only if you plan to send the generated audio to another platform after rendering.

tts skill FAQ

Is tts only for text to speech?

No. The tts skill also covers voice generation workflows such as voice cloning, subtitle-to-audio rendering, and voiceover creation. If your job is “make this text audible,” it fits; if your job is “write a script from scratch,” it does not.

Do I need coding experience to use it?

Not much, but you do need to provide structured input. Beginners can use tts if they can supply text, a file path, or an SRT and choose a basic output format. The more complex timeline and cloning features are easier when you understand what the script expects as input.

How is this different from a generic prompt?

A generic prompt can describe the task, but the tts skill gives you a reusable execution path, file handling, and backend-specific behavior. That reduces trial and error when you need consistent tts usage, especially for repeated voice generation jobs or when output format matters.

When should I not use tts?

Do not use tts if you only need an informal voice summary with no saved file, or if you cannot provide text, subtitles, or reference audio. It is also a poor fit when your goal is broad audio editing rather than speech synthesis.

How to Improve tts skill

Give the skill the right source material

The biggest quality gain comes from cleaner input. For narration, provide the final script with punctuation and paragraph breaks. For timeline work, supply an SRT with sensible segment lengths. For cloning or style matching, include a reference audio file or URL and say whether you want natural speech, a closer clone, or a more expressive delivery.

Specify constraints that affect rendering

If you care about tts for Voice Generation, say so directly and include the output format you need, such as WAV or OPUS. Mention timing constraints, language, speed, emotion, or whether the output is for direct playback or upload to another service. These details prevent the skill from choosing a path that sounds fine but fails your downstream use case.

Fix the common failure modes

The main failure modes are vague voice goals, overlong segments, and missing format requirements. If the result sounds rushed, shorten the text or split it into more segments before rerunning. If the voice is wrong, state whether you want neutral, warm, energetic, or cloned speech. If the file is unusable downstream, ask for the exact container or codec up front.

Iterate from the first render

Treat the first output as a draft. Improve it by changing the script text, not just the prompt: add pauses with punctuation, break up dense paragraphs, or refine SRT boundaries for cleaner timing. For timeline mode, the best iteration loop is usually: adjust segmenting, rerender, and only then tune voice or emotion settings.