A CLI + Web tool for speaker enrollment and identification using SpeechBrain.
Project description
08/08: a lot of improvements to the speaker-detector-client which resulted in a few changes to this backend.
23/07/2025 - Lara Whybrow, Creator - it has a few bugs that need fixing, but I ma determining if it is data related or software related. Feel free to clone from Github and help with bug fixes.
speaker-detector 🎙️
A lightweight CLI tool for speaker enrollment and voice identification, powered by SpeechBrain.
🔧 Features
- ✅ Enroll speakers from .wav audio
- 🕵️ Identify speakers from audio samples
- 🧠 ECAPA-TDNN embedding-based matching
- 🎛️ Simple, fast command-line interface
- 📁 Clean file storage in
~/.speaker-detector/ - 🔊 Optional
--verbosemode for debugging
Web UI note: The web client uses a guided-only enrollment flow (multiple short recordings). Quick enroll with a single clip has been removed to ensure model accuracy.
📦 Installation
pip install speaker-detector
When installing packages with a stale requirement file you might need to use: pip install --break-system-packages soundfile to install on WSL Ubuntu environment.
Run this version with -m module flag if you are having issues with running server.py:
python3 -m speaker_detector.server
🚀 Example Usage
🎙️ Enroll a speaker:
speaker-detector record --enroll Lara
🕵️ Identify a speaker:
speaker-detector record --test
📋 List enrolled speakers:
speaker-detector list
🗂️ Project Structure
~/.speaker-detector/enrollments/ Saved .pt voice embeddings ~/.speaker-detector/recordings/ CLI-recorded .wav audio files
🧹 Clean vs Verbose Mode By default, warnings from speechbrain, torch, etc. are hidden for a clean CLI experience. To enable full logs & deprecation warnings:
speaker-detector --verbose identify samples/test_sample.wav
🛠 Requirements Python 3.8+ torch speechbrain numpy soundfile onnxruntime
| Step | Command | When / Purpose | Output |
|---|---|---|---|
| 1. Export ECAPA Model to ONNX | speaker-detector export-model --pt models/embedding_model.ckpt --out ecapa_model.onnx |
Run once unless model changes | ecapa_model.onnx |
| 2. Enroll Speaker | speaker-detector enroll <speaker_id> <audio_path>Example: speaker-detector enroll Lara samples/lara1.wav |
Run per new speaker | Individual .pt files (e.g., Lara.pt) |
| 3. Combine Embeddings | speaker-detector combine --folder data/embeddings/ --out data/enrolled_speakers.pt |
After enrolling speakers | enrolled_speakers.pt |
| 4. Export Speakers to JSON | speaker-detector export-speaker-json --pt data/enrolled_speakers.pt --out public/speakers.json |
For frontend use | speakers.json |
| 5. Identify Speaker | speaker-detector identify samples/test_sample.wav |
Identify speaker from audio | Console output: name + score |
| 6. List Enrolled Speakers | speaker-detector list-speakers |
Show all enrolled speakers | Console output: list of IDs |
| Verbose Mode (optional) | Add --verbose to any command:speaker-detector --verbose identify samples/test_sample.wav |
Show warnings, detailed logs | Developer debug info |
NB: When pushing to Github, do not include any .identifier files.
You can manually clean up stale embeddings that don’t match any existing speaker folder with a quick script:
Run inside your project root
cd storage/embeddings for f in *.pt; do speaker="${f%.pt}" if [ ! -d "../speakers/$speaker" ]; then echo "Deleting stale embedding: $f" rm "$f" fi done
HTTP API: Online & Detection State
This backend exposes simple endpoints to let a client know when the server is reachable and when live detection is ready to be polled.
Online (one-shot SSE)
- Path:
GET /api/online - Headers:
Content-Type: text/event-streamCache-Control: no-cacheConnection: keep-aliveAccess-Control-Allow-Origin: http://localhost:5173(override with envCLIENT_ORIGIN)
- Behavior: immediately emits a single event and closes the stream.
Example event:
event: online
data: 1
This removes the need for heartbeat polling: as soon as the client connects, it can mark the backend as reachable.
Detection State (SSE)
- Path:
GET /api/detection-state - Emits an immediate state and then re-emits on changes; includes keep-alives.
- Event name:
detection - Data:
running|stopped
Example stream excerpts:
event: detection
data: stopped
: keep-alive
event: detection
data: running
Clients can start polling /api/active-speaker only when the state is running, and pause when stopped.
Active Speaker (readiness semantics)
- Path:
GET /api/active-speaker - Responses:
- When listening mode is OFF:
200 { "status": "disabled", "speaker": null, "confidence": null, "is_speaking": false } - When mode is ON but engine not yet ready (e.g., mic unavailable or loop not running):
200 { "status": "pending", ... } - When running and healthy:
200with the usual payload includingspeaker,confidence,is_speaking,status: "listening", and optionalsuggested.
- When listening mode is OFF:
These semantics avoid red 503s in DevTools while still making state transitions explicit for the client.
Quick Examples
Curl (SSE streams)
# One-shot online event
curl -N -H 'Accept: text/event-stream' http://127.0.0.1:9000/api/online
# Detection state stream (emits running|stopped)
curl -N -H 'Accept: text/event-stream' http://127.0.0.1:9000/api/detection-state
Browser client (minimal)
// Reachability: mark backend online as soon as server is up
const online = new EventSource('http://127.0.0.1:9000/api/online');
online.addEventListener('online', () => {
console.log('Backend online');
online.close(); // one-shot
});
// Detection state: start/stop polling active speaker
let pollTimer = null;
function startPolling() {
if (pollTimer) return;
pollTimer = setInterval(async () => {
try {
const r = await fetch('http://127.0.0.1:9000/api/active-speaker');
const j = await r.json();
if (j.status === 'disabled' || j.status === 'pending') return; // wait
console.log('Active:', j);
} catch (e) {
console.warn('poll failed', e);
}
}, 500);
}
function stopPolling() { clearInterval(pollTimer); pollTimer = null; }
const detect = new EventSource('http://127.0.0.1:9000/api/detection-state');
detect.addEventListener('detection', (ev) => {
const state = (ev.data || '').trim();
if (state === 'running') startPolling(); else stopPolling();
});
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