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Skillsbench TTS Audio Mastering

Practical mastering steps for TTS audio: cleanup, loudness normalization, alignment, and delivery specs.

install
source · Clone the upstream repo
git clone https://github.com/benchflow-ai/skillsbench
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/benchflow-ai/skillsbench "$T" && mkdir -p ~/.claude/skills && cp -r "$T/tasks/multilingual-video-dubbing/environment/skills/text-to-speech" ~/.claude/skills/benchflow-ai-skillsbench-tts-audio-mastering && rm -rf "$T"
manifest: tasks/multilingual-video-dubbing/environment/skills/text-to-speech/SKILL.md
source content

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.