Full-day voice-stack refactor. Experiments run and reverted:
- Gemini Live HTTP microservice (Python 3.8 env incompat, latency)
- Vosk grammar STT (English lexicon can't decode 'Sanad'; big model
cold-load too slow on Jetson CPU)
Kept architecture:
- Voice/wake_detector.py — pure-numpy energy state machine with
adaptive baseline, burst-audio capture for post-hoc verify.
- Voice/marcus_voice.py — orchestrator with 3 modes
(wake_and_command / always_on / always_on_gated), hysteretic VAD,
pre-silence trim (300 ms pre-roll), DSP pipeline (DC remove,
80 Hz HPF, 0.97 pre-emphasis, peak-normalize), faster-whisper
base.en int8 with beam=8 + temperature fallback [0,0.2,0.4],
fuzzy-match canonicalisation, GARBAGE_PATTERNS + length filter,
/s-/ phonetic wake-verify, full-turn debug WAV recording.
Config-driven vocab (zero hardcoded strings in Python):
- stt.wake_words (33 variants of 'Sanad')
- stt.command_vocab (68 canonical phrases)
- stt.garbage_patterns (17 Whisper noise outputs)
- stt.min_transcription_length, stt.command_vocab_cutoff
Command parser widened (Brain/command_parser.py):
- _RE_SIMPLE_DIR — bare direction + verb+direction combos
('left', 'go back', 'move forward', 'step right', ...)
- _RE_STOP_SIMPLE — bare stop/halt/wait/pause/freeze/hold
- All motion constants sourced from config_Navigation.json
(move_map + step_duration_sec) via API/zmq_api.py; no more
hardcoded 0.3 / 2.0 magic numbers.
API/audio_api.py — _play_pcm now uses AudioClient.PlayStream with
automatic resampling to 16 kHz (matches Sanad's proven pattern).
Removed:
- Voice/vosk_stt.py (and all Vosk references in marcus_voice.py)
- Models/vosk-model-small-en-us-0.15/ (40 MB model + zip)
- All Vosk keys from Config/config_Voice.json
Documentation synced across README, Doc/architecture.md,
Doc/pipeline.md, Doc/functions.md, Doc/controlling.md,
Doc/MARCUS_API.md, Doc/environment.md changelog.
Known limitation: faster-whisper base.en on Jetson CPU + G1
far-field mic yields ~50% command-transcription accuracy due
to model capacity and mic reverberation. Wake + ack + recording
+ trim + Whisper + fuzzy + brain + motion all verified working
end-to-end. Future improvement path (unused): close-talking USB
mic via pactl_parec, or Gemini Live via HTTP microservice.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
399 lines
15 KiB
Python
399 lines
15 KiB
Python
#!/usr/bin/env python3
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"""
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API/audio_api.py — Marcus Audio API Layer
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==========================================
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Provides speak() and record() for the Brain layer.
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Brain imports ONLY from this API — never from unitree SDK directly.
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Speaker: Unitree built-in TtsMaker (G1 on-board engine, English only,
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no MP3/WAV plumbing, no internet). Optional raw-PCM playback path
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via _play_pcm() is kept for future modules that synthesize their
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own audio (e.g. offline Piper).
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Mic: G1 built-in mic (UDP multicast 239.168.123.161:5555, 16 kHz mono).
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Legacy Hollyland/parec path retained as fallback when
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config_Voice.json has mic.backend="pactl_parec".
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TTS: English only. Arabic is rejected (the G1 firmware silently maps
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Arabic to Chinese, which confuses everyone — if Arabic TTS is ever
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needed again, use a separate offline backend like Piper).
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Usage:
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from API.audio_api import AudioAPI
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audio = AudioAPI()
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audio.speak("Hello, I am Sanad")
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recording = audio.record(seconds=5)
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audio.play_pcm(recording)
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"""
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import json
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import logging
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import os
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import subprocess
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import sys
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import threading
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import time
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import wave
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from logging.handlers import RotatingFileHandler
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import numpy as np
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# ─── PATH + CONFIG ───────────────────────────────────────
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# Use the canonical loaders from Core/ so path + config logic lives in one place.
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_PROJECT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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if _PROJECT_DIR not in sys.path:
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sys.path.insert(0, _PROJECT_DIR)
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from Core.env_loader import PROJECT_ROOT
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from Core.config_loader import load_config
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LOG_DIR = os.path.join(PROJECT_ROOT, "logs")
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os.makedirs(LOG_DIR, exist_ok=True)
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# All voice-subsystem logs go ONLY to logs/voice.log, not stdout — the
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# terminal REPL needs a clean `Command:` prompt. Anything the operator
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# needs to see is print()-ed explicitly from the callback sites.
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# basicConfig is idempotent (no-op if marcus_voice installed handlers first).
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(name)s] %(levelname)s: %(message)s",
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handlers=[
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RotatingFileHandler(
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os.path.join(LOG_DIR, "voice.log"),
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maxBytes=5_000_000, backupCount=3, encoding="utf-8",
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),
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],
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)
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log = logging.getLogger("audio_api")
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# ─── AUDIO API CLASS ─────────────────────────────────────
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class AudioAPI:
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"""Marcus audio interface — speak + record + play."""
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def __init__(self):
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self._config = load_config("Voice")
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self._client = None
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self._sdk_available = False
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self._init_sdk()
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# Config shortcuts
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self._tts = self._config["tts"]
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self._mic = self._config["mic"]
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self._spk = self._config["speaker"]
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self._target_rate = self._tts.get("target_sample_rate", 16000)
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# Default mic backend: G1 built-in UDP multicast.
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# Set mic.backend="pactl_parec" in config_Voice.json to fall back
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# to the legacy Hollyland/PulseAudio path.
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self._mic_backend = self._mic.get("backend", "builtin_udp")
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self._builtin_mic = None # lazy-initialized on first record()
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# Built-in TTS wrapper (uses the already-initialized AudioClient).
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# Keeps TTS synchronous so `is_speaking` is meaningful to the voice
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# loop that needs to skip mic input during playback.
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self._tts_engine = None
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if self._sdk_available:
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from Voice.builtin_tts import BuiltinTTS
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self._tts_engine = BuiltinTTS(
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self._client,
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default_speaker_id=self._tts.get("builtin_speaker_id", 0),
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)
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# Data dir
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data_dir = os.path.join(PROJECT_ROOT, self._config["audio"]["data_dir"])
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os.makedirs(data_dir, exist_ok=True)
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self._data_dir = data_dir
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# Speaking lock — prevents mic from hearing TTS output
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self._speaking = False
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self._speak_lock = threading.Lock()
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log.info("%s (mic=%s, tts=%s)",
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self._config["messages"]["ready"],
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self._mic_backend,
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"builtin_ttsmaker" if self._tts_engine else "disabled")
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def _init_sdk(self):
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"""Initialize Unitree AudioClient."""
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try:
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from unitree_sdk2py.core.channel import ChannelFactoryInitialize
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from unitree_sdk2py.g1.audio.g1_audio_client import AudioClient
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dds_iface = self._config["speaker"]["dds_interface"]
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ChannelFactoryInitialize(0, dds_iface)
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self._client = AudioClient()
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self._client.SetTimeout(10.0)
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self._client.Init()
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self._client.SetVolume(self._config["speaker"]["volume"])
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self._sdk_available = True
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log.info("AudioClient initialized on %s", dds_iface)
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except Exception as e:
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log.error("AudioClient init failed: %s", e)
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self._sdk_available = False
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# ─── SPEAK ────────────────────────────────────────────
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def speak(self, text: str, lang: str = "en"):
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"""
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Speak `text` in English through the G1 built-in TTS (TtsMaker).
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Mutes (flushes) the mic during playback so the voice loop doesn't
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hear the robot's own voice and transcribe itself. `lang` is kept
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in the signature for API compatibility but only `"en"` is accepted
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— non-ASCII text (Arabic) is rejected by BuiltinTTS because the
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G1 firmware silently maps it to Chinese, which nobody wants.
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"""
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if lang and lang != "en":
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log.warning("builtin_tts only supports English; got lang=%r — skipping", lang)
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return
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if self._tts_engine is None:
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log.error("No TTS engine initialized — audio SDK unavailable")
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return
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log.info("speak: %s", text[:80])
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with self._speak_lock:
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self._speaking = True
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self._mute_mic()
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try:
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self._tts_engine.speak(text, block=True)
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except Exception as e:
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log.error("%s: %s", self._config["messages"]["error_tts"], e)
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finally:
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# Small tail so the speaker fully finishes before the mic is
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# re-opened for capture
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time.sleep(0.2)
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self._unmute_mic()
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self._speaking = False
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def _mute_mic(self):
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"""
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Suppress mic input during TTS playback.
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For the UDP built-in mic, flush the buffer so we don't capture any
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echo that's already been queued. For the legacy PulseAudio path,
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actually mute the source.
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"""
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if self._mic_backend == "builtin_udp":
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if self._builtin_mic is not None:
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self._builtin_mic.flush()
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return
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source = self._mic["source_index"]
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subprocess.run(["pactl", "set-source-mute", source, "1"],
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capture_output=True)
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log.debug("Mic muted")
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def _unmute_mic(self):
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"""Re-enable mic after TTS playback (pactl path only)."""
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if self._mic_backend == "builtin_udp":
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if self._builtin_mic is not None:
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self._builtin_mic.flush()
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return
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source = self._mic["source_index"]
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subprocess.run(["pactl", "set-source-mute", source, "0"],
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capture_output=True)
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log.debug("Mic unmuted")
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@property
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def is_speaking(self) -> bool:
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"""True while TTS is playing — voice module checks this."""
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return self._speaking
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def _resample(self, audio: np.ndarray, src_rate: int) -> np.ndarray:
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"""Linear resample int16 PCM to self._target_rate (16 kHz)."""
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if src_rate == self._target_rate:
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return audio
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tl = int(len(audio) * self._target_rate / src_rate)
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return np.interp(
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np.linspace(0, len(audio), tl, endpoint=False),
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np.arange(len(audio)),
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audio.astype(np.float64),
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).astype(np.int16)
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# ─── G1 SPEAKER PLAYBACK (raw PCM, kept for future backends) ─────────
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def _play_pcm(self, audio: np.ndarray, rate: int = None) -> float:
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"""
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Play mono int16 PCM on the G1 speaker.
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`rate` is the sample rate of the incoming `audio`; we always
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resample to self._target_rate (16 kHz) before sending because the
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G1 speaker hardware only honors that rate — if you hand it 24 kHz
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PCM, it plays ~1.5x too fast. This matches the Sanad pattern.
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Uses AudioClient.PlayStream (the high-level API) with a fresh
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stream_id + STOP_PLAY bracket on either side so a prior stream
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can't blend into this one.
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"""
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if not self._sdk_available:
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log.warning("SDK not available, cannot play audio")
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return 0.0
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src_rate = int(rate) if rate else self._target_rate
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audio = self._resample(audio, src_rate) # → self._target_rate
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if audio.size == 0:
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return 0.0
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from unitree_sdk2py.g1.audio.g1_audio_api import ROBOT_API_ID_AUDIO_STOP_PLAY
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app_name = self._spk["app_name"]
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# Stop any prior stream before opening a new one.
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self._client._Call(
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ROBOT_API_ID_AUDIO_STOP_PLAY,
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json.dumps({"app_name": app_name}),
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)
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time.sleep(0.15)
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sid = f"s_{int(time.time() * 1000)}"
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self._client.PlayStream(app_name, sid, audio.tobytes())
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duration = len(audio) / self._target_rate
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# Margin covers DDS buffer drain before STOP cuts playback short.
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time.sleep(duration + 0.3)
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self._client._Call(
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ROBOT_API_ID_AUDIO_STOP_PLAY,
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json.dumps({"app_name": app_name}),
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)
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log.info("Played: %.1fs (src=%d Hz → hw=%d Hz)",
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duration, src_rate, self._target_rate)
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return duration
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def play_pcm(self, audio: np.ndarray, rate: int = None) -> float:
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"""Public wrapper for playing PCM audio."""
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return self._play_pcm(audio, rate=rate)
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# ─── MIC RECORDING ───────────────────────────────────
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def record(self, seconds: float = 5.0) -> np.ndarray:
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"""
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Capture `seconds` of int16 mono 16 kHz PCM.
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Default backend is the G1 built-in mic (UDP multicast). Set
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mic.backend="pactl_parec" in config_Voice.json to use the
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legacy Hollyland/parec path instead.
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"""
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if self._mic_backend == "builtin_udp":
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return self._record_builtin(seconds)
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return self._record_parec(seconds)
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def _record_builtin(self, seconds: float) -> np.ndarray:
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"""Built-in mic path — join UDP multicast, read the requested duration."""
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if self._builtin_mic is None:
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from Voice.builtin_mic import BuiltinMic
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mcfg = self._config.get("mic_udp", {})
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self._builtin_mic = BuiltinMic(
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group=mcfg.get("group", "239.168.123.161"),
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port=mcfg.get("port", 5555),
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buf_max=mcfg.get("buffer_max_bytes", 64000),
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)
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self._builtin_mic.start()
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time.sleep(0.2) # let the receiver thread fill in
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log.info("Recording %.1fs from G1 built-in mic", seconds)
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raw = self._builtin_mic.read_seconds(seconds)
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audio = np.frombuffer(raw, dtype=np.int16)
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log.info("Recorded: %d samples, std=%.0f", len(audio), audio.std())
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if audio.std() < 50:
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log.warning(self._config["messages"]["error_mic"] +
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" — G1 mic silent (check audio service on robot)")
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return audio
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def _record_parec(self, seconds: float) -> np.ndarray:
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"""Legacy Hollyland/PulseAudio path — only used if mic.backend='pactl_parec'."""
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source = self._mic["source_index"]
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rate = str(self._mic["rate"])
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channels = str(self._mic["channels"])
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fmt = self._mic["format"]
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subprocess.run(["pactl", "set-source-mute", source, "0"], capture_output=True)
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subprocess.run(["pactl", "set-source-volume", source, "100%"], capture_output=True)
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log.info("Recording %.1fs from mic source %s (parec)", seconds, source)
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proc = None
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raw = b""
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try:
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proc = subprocess.Popen(
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["parec", "-d", source,
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f"--format={fmt}", f"--rate={rate}", f"--channels={channels}", "--raw"],
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stdout=subprocess.PIPE,
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)
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time.sleep(seconds)
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finally:
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# Always kill parec — an exception in time.sleep (Ctrl-C / signal)
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# would otherwise leave an orphaned recorder process running.
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if proc is not None:
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try:
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proc.terminate()
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raw = proc.stdout.read()
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proc.wait(timeout=1.0)
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except Exception as e:
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log.warning("parec cleanup error: %s", e)
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# Last-resort SIGKILL — suppress only OSError (process
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# already exited) so we don't mask other bugs.
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try:
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proc.kill()
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except OSError:
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pass
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audio = np.frombuffer(raw, dtype=np.int16)
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log.info("Recorded: %d samples, std=%.0f", len(audio), audio.std())
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if audio.std() < 50:
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log.warning(self._config["messages"]["error_mic"] + " — mic may be silent")
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return audio
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def save_recording(self, audio: np.ndarray, name: str) -> str:
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"""Save recording to Data/Voice/Recordings/."""
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path = os.path.join(self._data_dir, f"{name}.wav")
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wf = wave.open(path, "wb")
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(self._target_rate)
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wf.writeframes(audio.tobytes())
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wf.close()
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log.info("Saved: %s", path)
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return path
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# ─── STATUS ───────────────────────────────────────────
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@property
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def is_available(self) -> bool:
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return self._sdk_available
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# ─── STANDALONE TEST ─────────────────────────────────────
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description="Marcus Audio API Test")
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parser.add_argument("--test", action="store_true", help="Run TTS + record test")
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parser.add_argument("--speak", type=str, help="Speak this English text")
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parser.add_argument("--record", type=float, default=0, help="Record N seconds")
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args = parser.parse_args()
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api = AudioAPI()
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if args.test:
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print("\n--- English (TtsMaker) ---")
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api.speak("Hello, I am Sanad.")
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time.sleep(1)
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print("\n--- Record 3s + playback ---")
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rec = api.record(3.0)
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if rec.std() > 50:
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api.play_pcm(rec)
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print("\nDone.")
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elif args.speak:
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api.speak(args.speak)
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elif args.record > 0:
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rec = api.record(args.record)
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api.save_recording(rec, f"test_{int(time.time())}")
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if rec.std() > 50:
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api.play_pcm(rec)
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else:
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parser.print_help()
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