Assistant vocal local ESP32 : étapes 1 à 15, et 15b écrite

État du projet au premier commit :
- firmware ESP32 : micro I2S, lecture anti-gigue, MQTT (état retenu, testament),
  mains libres, domotique de démonstration, chien de garde, présence du serveur ;
- serveur Python : sessions, VAD, faster-whisper, pyannote, identification,
  droits par profil, domotique, mot de réveil, Piper ;
- broker Mosquitto : configuration, comptes et ACL (non activés en développement) ;
- étape 15b écrite, en attente d'essai : agent MQTT pour machines Linux.

Étapes 1 à 15 validées. 203 tests, pyright sans erreur.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

server/tests/test_speaker_attribution.py

@@ -0,0 +1,65 @@
+"""Tests de l'association locuteur + texte, étape 10 (sans modèle)."""
+
+from __future__ import annotations
+
+import json
+import math
+
+from voice_server.diarization import SpeakerTurn
+from voice_server.speaker_attribution import Utterance, attribute, transcript_json, turn_of
+from voice_server.speaker_identifier import Identification
+from voice_server.speech_to_text import Word
+
+# Mots et tours relevés sur la session réelle 453cce (vous, un haut-parleur, vous).
+WORDS = [Word(" Ouvrir", 0.00, 0.56), Word(" la", 0.56, 0.76), Word(" porte.", 0.76, 1.26),
+         Word(" Je", 1.50, 1.66), Word(" suis", 1.66, 1.78), Word(" là.", 1.78, 1.92),
+         Word(" Fermez", 4.92, 5.38), Word(" la", 5.38, 5.52), Word(" porte.", 5.52, 5.86)]
+TURNS = [SpeakerTurn("SPEAKER_00", 0.08, 1.50), SpeakerTurn("SPEAKER_01", 1.57, 4.69),
+         SpeakerTurn("SPEAKER_00", 4.92, 6.17)]
+VERDICTS = {"SPEAKER_00": Identification("Denis", 0.72, "Denis"),
+            "SPEAKER_01": Identification(None, -0.05, "Denis")}
+
+
+def test_word_goes_to_the_most_overlapping_turn() -> None:
+    """« Je » (1,50-1,66) touche SPEAKER_00 sur 0 s et SPEAKER_01 sur 0,09 s."""
+    turn = turn_of(Word(" Je", 1.50, 1.66), TURNS)
+    assert turn is not None and turn.speaker == "SPEAKER_01"
+
+
+def test_word_in_a_gap_goes_to_the_nearest_turn() -> None:
+    """Un mot entre deux tours va au plus proche : jamais perdu."""
+    before = turn_of(Word(" euh", 4.70, 4.76), TURNS)  # 0,04 s après la fin de SPEAKER_01
+    after = turn_of(Word(" euh", 4.84, 4.90), TURNS)   # 0,05 s avant la reprise de SPEAKER_00
+    assert before is not None and before.speaker == "SPEAKER_01"
+    assert after is not None and after.start_s == 4.92
+
+
+def test_real_session_is_split_by_speaker() -> None:
+    utterances = attribute(WORDS, TURNS, VERDICTS)
+
+    assert [(u.speaker, u.text) for u in utterances] == [
+        ("Denis", "Ouvrir la porte."), ("Inconnu", "Je suis là."), ("Denis", "Fermez la porte.")]
+    assert (utterances[0].start_s, utterances[0].end_s) == (0.0, 1.26)
+    assert utterances[1].label == "SPEAKER_01" and utterances[1].score == -0.05
+
+
+def test_without_diarization_everything_is_one_unknown_utterance() -> None:
+    [utterance] = attribute(WORDS, [], {})
+
+    assert utterance.speaker == "Inconnu" and utterance.score is None
+    assert utterance.text == "Ouvrir la porte. Je suis là. Fermez la porte."
+
+
+def test_speaker_with_too_little_speech_has_no_score() -> None:
+    """Empreinte impossible (NaN) : « Inconnu », score null dans le JSON."""
+    [utterance] = attribute(WORDS[:1], TURNS[:1], {"SPEAKER_00": Identification(None, math.nan, None)})
+    assert utterance.speaker == "Inconnu" and utterance.score is None
+
+
+def test_json_message() -> None:
+    """Le format attendu par la feuille de route : {"speaker": ..., "text": ...}, accents lisibles."""
+    payload = transcript_json("a1b2c3", [Utterance("Élodie", "Ferme la porte.", 0.0, 1.234, 0.7456)])
+
+    assert json.loads(payload) == {"session": "a1b2c3", "utterances": [
+        {"speaker": "Élodie", "text": "Ferme la porte.", "start": 0.0, "end": 1.23, "score": 0.75}]}
+    assert "Élodie".encode() in payload