sl-jetson
a9b2242a2c
- Dockerfile.social: social-bot container with faster-whisper, llama-cpp-python (CUDA), piper-tts, insightface, pyannote.audio, OpenWakeWord, pyaudio - scripts/convert_models.sh: TRT FP16 conversion for SCRFD-10GF, ArcFace-R100, ECAPA-TDNN; CTranslate2 setup for Whisper; Piper voice download; benchmark suite - config/asound.conf: ALSA USB mic (card1) + USB speaker (card2) config - models/README.md: version-pinned model table, /models/ layout, perf targets - systemd/: saltybot-social.service + saltybot.target + install_systemd.sh - docker-compose.yml: saltybot-social service with GPU, audio device passthrough, NVMe volume mounts for /models and /social_db Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
39 lines
685 B
Plaintext
39 lines
685 B
Plaintext
# ALSA config for social-bot audio
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# Assumes USB mic (ReSpeaker or similar) at card 1, USB speaker at card 2
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# Adjust card numbers with: aplay -l / arecord -l
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# Default capture device — USB mic array (ReSpeaker 2-Mic or 4-Mic)
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pcm.!default {
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type asym
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playback.pcm "usb_speaker"
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capture.pcm "usb_mic"
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}
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# USB microphone input
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pcm.usb_mic {
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type plug
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slave {
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pcm "hw:1,0"
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rate 16000
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channels 1
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format S16_LE
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}
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}
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# USB speaker output
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pcm.usb_speaker {
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type plug
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slave {
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pcm "hw:2,0"
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rate 22050
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channels 1
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format S16_LE
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}
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}
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# Mixer controls
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ctl.!default {
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type hw
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card 1
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}
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