docs: add demo audio + comparison table to README (#21)

Two visibility wins for the public face of the repo:

 - docs/demo.wav: 5 seconds of two stackvox voices (af_heart and
   bf_emma) speaking the tagline, generated locally with the cached
   Kokoro model. 234 KB at 24kHz PCM_16 — small enough to commit and
   serve via the GitHub raw URL. Linked from the top of the README so
   first-time visitors can hear the tool without installing anything.

 - README "How does this compare to other TTS?" section comparing
   stackvox against `say`, `espeak-ng`, Piper, Coqui TTS, and the
   cloud APIs across offline/quality/latency/license. The honest
   pitch: voice quality alone isn't a reason to switch off Piper, but
   the resident daemon plus bash helper for sub-15ms shell-side speech
   is the differentiator for shell-driven workflows.

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: StuBehan

.gitignore

@@ -8,6 +8,7 @@ dist/
 *.bin
 out/
 *.wav
+!docs/demo.wav
 .DS_Store
 .env
 .coverage

README.md

@@ -7,6 +7,8 @@
 
 Offline TTS using [Kokoro-82M](https://huggingface.co/hexgrad/Kokoro-82M) via [kokoro-onnx](https://github.com/thewh1teagle/kokoro-onnx). Apache 2.0 model, ~340MB, CPU real-time, plays straight to system audio. Designed to be importable as a Python library, drivable as a CLI, or poked via a unix socket for ~13ms speech requests from shell scripts.
 
+🔊 **Hear it:** [docs/demo.wav](./docs/demo.wav) — five seconds of two voices speaking the tagline (`af_heart` then `bf_emma`).
+
 ## Install
 
 From PyPI — recommended for most users:
@@ -178,6 +180,23 @@ Model weights (`kokoro-v1.0.onnx`, ~340 MB) and voices are downloaded from the [
 
 Security issues themselves should not be filed as public GitHub issues — see [`SECURITY.md`](./SECURITY.md) for the disclosure process.
 
+## How does this compare to other TTS?
+
+stackvox is a fairly opinionated narrow slice of the TTS space. Here's where it sits next to the obvious neighbours:
+
+| Tool | Offline? | Quality | Latency (typical) | License | Best for |
+|---|---|---|---|---|---|
+| **stackvox** (Kokoro-82M) | ✅ | High (24kHz, 50+ voices, 9 languages) | ~300ms in-process · ~13ms via daemon helper | Apache 2.0 | Local apps, shell hooks, anything that wants natural voice without the cloud |
+| macOS `say` | ✅ | OK | ~50ms | macOS only | macOS-only scripts, "good enough" voice |
+| `espeak-ng` | ✅ | Robotic | ~10ms | GPL-3.0 | Accessibility, screen readers, embedded |
+| [Piper](https://github.com/rhasspy/piper) | ✅ | High | ~100ms | MIT | Similar use-case to stackvox; ONNX-based, more voices in some languages |
+| [Coqui TTS](https://github.com/coqui-ai/TTS) | ✅ | Very high (research models) | seconds | MPL-2.0 | Research, fine-tuning, voice cloning |
+| OpenAI / ElevenLabs / etc. | ❌ | Highest | network-bound | Proprietary | Production apps that can pay per-call and accept network dependency |
+
+Where stackvox tries to be different from Piper specifically: a **resident daemon + bash helper** path that gets you sub-15ms speech requests from shell scripts (CI hooks, terminal notifications, status announcements) without paying Python's startup cost on every call. That's basically the point — voice quality alone wouldn't be enough to switch off Piper, but the IPC story makes a difference for shell-driven workflows.
+
+Pick stackvox if you want **good voices, fully offline, with a fast shell-friendly API**.
+
 ## License & attributions
 
 stackvox itself is licensed under the **Apache License, Version 2.0** — see [`LICENSE`](./LICENSE). Third-party attributions are collected in [`NOTICE`](./NOTICE); the summary below is informational.