Skip to main content
ZombieMutex

30 results · ↑ ↓ navigate · Enter open · Esc close

← All projects

Project notebook / Audio ML

Implemented

Text-to-Speech & Prosody Pipeline

I built an utterance segmentation and prosody-planning pipeline with per-chunk speaking rates and sentence-type F0 targets, connected to real offline macOS text-to-speech rendering.

Discuss this project

What I built

  • Implemented sentence segmentation and reproducible declarative prosody plans for questions, statements and emphatic responses.
  • Implemented per-segment speaking-rate decisions and target pitch contours, represented separately from the synthesis engine.
  • Integrated offline macOS speech rendering to AIFF files and validated output creation without external TTS accounts or API costs.

Experiments & checks

  • The local pipeline renders actual speech through macOS `say`. The rate setting is applied per chunk; the F0 curves are separate planning metadata and do not control the system synthesizer's pitch. The distinction matters because the control interface defines what expressive synthesis can actually deliver.

Notes & limitations

Readable text is not automatically natural speech. Questions, emphasis, phrasing, pauses and speaker consistency affect how a caller experiences an answer, especially under strict turn-taking deadlines.

I did not train a neural TTS foundation model or claim emotion-, prosody- or multi-speaker-controllable synthesis with macOS `say`. Target pitch contours are prepared for a future controllable model adapter, not applied to current rendered speech.

Punctuation does not come with an acoustic renderer. A question mark deserves more than being pronounced as a period with ambition.

Screenshots & media

Screenshot of the public ZombieMutex page for Text-to-Speech & Prosody Pipeline
Preview of the public project page or browser lab. This is not a screenshot of a private customer system. View full size ↗

Project updates

Dated notes tied to actual revisions of the site, not a simulated activity feed.

  1. Audio experiments published

    Added five implemented audio-ML projects with local experiments and measurement limits.

    Site revision 8d75d02

These entries reflect published changes to this website. The website repository is private; revision IDs are not public source links.

Discuss this project

Questions, ideas, minimal reproductions and corrections are welcome. Each project has its own public GitHub Discussion.

You can read without an account; posting requires GitHub sign-in. Keep private customer information, credentials and restricted material out of public threads.

Open this project's discussion