# Benchflow AI Skillsbench Text To Speech > SKILL: TTS Audio Mastering - Skill: `tomevault-io/benchflow-ai-skillsbench-text-to-speech` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/benchflow-ai-skillsbench-text-to-speech` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/benchflow-ai-skillsbench-text-to-speech/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/benchflow-ai-skillsbench-text-to-speech --- # SKILL: TTS Audio Mastering This skill focuses on producing clean, consistent, and delivery-ready TTS audio for video tasks. It covers speech cleanup, loudness normalization, segment boundaries, and export specs. ## 1. TTS Engine & Output Basics Choose a TTS engine based on deployment constraints and quality needs: * **Neural offline** (e.g., Kokoro): stable, high quality, no network dependency. * **Cloud TTS** (e.g., Edge-TTS / OpenAI TTS): convenient, higher naturalness but network-dependent. * **Formant TTS** (e.g., espeak-ng): for prototyping only; often less natural. **Key rule:** Always confirm the **native sample rate** of the generated audio before resampling for video delivery. --- ## 2. Speech Cleanup (Per Segment) Apply lightweight processing to avoid common artifacts: * **Rumble/DC removal:** high-pass filter around **20 Hz** * **Harshness control:** optional low-pass around **16 kHz** (helps remove digital fizz) * **Click/pop prevention:** short fades at boundaries (e.g., **50 ms** fade-in and fade-out) Recommended FFmpeg pattern (example): * Add filters in a single chain, and keep them consistent across segments. --- ## 3. Loudness Normalization Target loudness depends on the benchmark/task spec. A common target is ITU-R BS.1770 loudness measurement: * **Integrated loudness:** **-23 LUFS** * **True peak:** around **-1.5 dBTP** * **LRA:** around **11** (optional) Recommended workflow: 1. **Measure loudness** using FFmpeg `ebur128` (or equivalent meter). 2. **Apply normalization** (e.g., `loudnorm`) as the final step after cleanup and timing edits. 3. If you adjust tempo/duration after normalization, re-normalize again. --- ## 4. Timing & Segment Boundary Handling When stitching segment-level TTS into a full track: * Match each segment to its target window as closely as possible. * If a segment is shorter than its window, pad with silence. * If a segment is longer, use gentle duration control (small speed change) or truncate carefully. * Always apply boundary fades after padding/trimming to avoid clicks. **Sync guideline:** keep end-to-end drift small (e.g., **<= 0.2s**) unless the task states otherwise. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/benchflow-ai) — claim your Tome and manage your conversions.