Scenario Overview
Turnkey edge solution: on-device audio + local ASR/TTS + multi-lang dialogue. Covers desktop, industrial & smart home. Off-the-shelf modules, fast to market; custom hardware optional.
End-to-End Low Latency
End-to-End Low Latency
  • 0.3–0.5s E2E, impossible for cloud
  • One-time hardware, no per-call fees
  • Rock-steady — network stays stable
Multi-lang Out of the Box
Multi-lang Out of the Box
  • Major languages, zero config needed
  • Machine, Simulated, or Human voice
  • Clone any voice with ~10s of audio
Edge Benefits, Multi Win
Edge Benefits, Multi Win
  • Text-only upload reduces cloud costs
  • Voice stays on-device, fully private
  • No cloud: region, rate, or shutdown
  • Works offline or on weak networks
Application Scenarios
Desktop Voice AI

Multi-lang ASR · Interpreting · Natural TTS

On-device multi-lang recognition, real-time translation & natural TTS. Deploy on desktop, meeting terminals, guide kiosks for two-way dialogue & cross-language communication.


Core Advantages

  • Multilingual Recognition: Major languages ready out of the box
  • Simultaneous Interpretation: Listen-and-translate w/ 0.3–0.5s E2E latency
  • Tiered Voice Quality: Machine / Simulated / Human — pick by budget
Scene Feature
Multilingual Recognition
Multi-lang ready w/ zero setup
Scene Feature
Simultaneous Interpretation
Real-time translate w/ low latency
Scene Feature
Voice Persona
Tiered voices; clone ~10s sample
Industrial Voice

Voice device control & field data entry

Voice replaces UIs & scanners in warehouses & workshops. Workers use natural language for logging, inspection, patrol forms & alerts. Local ASR outputs structured text for WMS, MES & IoT.


Core Advantages

  • Lower Op Barrier: Natural language replaces UIs, scanners & work-order apps
  • Weak-Network Ready: Local ASR w/ text backhaul — independent of on-site bandwidth
  • Structured Output: Results feed directly into WMS, MES & work-order systems
Scene Feature
Warehouse Inbound/Outbound
Voice verify SKU → direct WMS write
Scene Feature
Equipment Inspection
Voice equip check auto-fills forms
Scene Feature
Patrol Reporting & Alerts
Voice patrol forms & hazard alerts
Smart Home Assistant

Instant Wake · Local Control · Voiceprint

XIAO ESP32S3 low-power wake frontend triggers ASR-TTS on AI box. Voiceprint ID for per-member preferences. Integrates w/ Matter, HomeAssistant, Mi Home. Fully local — offline won't disrupt use.


Core Advantages

  • Ultra-low standby: wakes the main unit only on the wake word — months per charge
  • Voiceprint: Identify members & load personal preferences
  • Local Control: Integrated w/ Matter, HomeAssistant, Mi Home & more
Scene Feature
Low-Power Wake
Low-power wake word on ESP32S3
Scene Feature
Voiceprint Member Recognition
Voiceprint → auto scene settings
Scene Feature
Local IoT Orchestration
Matter/HA/Mi Home local control
Deployment & Selection
Architecture

Three Models: Frontend, Hybrid, All-in-One

Voice compute placement determines capability ceiling & per-unit BOM. Three common models:


Core Advantages

  • Frontend (ESP32S3): Low-power wake & simple commands; pair w/ your host system
  • Hybrid (Frontend + Box): Edge wakes + ASR + TTS; LLM remote. Best value.
  • All-in-One (High-End): Single Jetson, full ASR/TTS/LLM. Privacy & offline.
ImageHardwareVoice Concurrency (voice-only)Voice CapabilitiesLocal LLM
reRouter CM4 SeriesreRouter CM4 Series1 channelMachine VoiceCloud optional
reComputer RK3576 SeriesreComputer RK3576 Series1 channelSimulated Voice4B–7B (w/ 1282 accel)
reComputer RK3588 SeriesreComputer RK3588 Series1 channelSimulated Voice4B–7B (w/ 1282 accel)
reComputer J30 SeriesreComputer J30 Series1 channelNatural Voice~2B
reComputer J40 SeriesreComputer J40 Series2–3 channelsNatural Voice4B–7B
reComputer J50 SeriesreComputer J50 Series3+ channelsNatural Voice7B–14B
NVIDIA Jetson AGX Thor Developer KitNVIDIA Jetson AGX Thor Developer Kit6+ concurrent (voice-only)Realistic voice14B–32B

Choose AI Compute Box by Capability

Compute boxes are tiered by voice capabilities. The table below is the device list for this scenario (by family): voice-only concurrency, voice capability, and deployable local-LLM size per family. Pick exact models, configurations, and accessories in the configurator below (see next tab for mic & speaker selection). Note: running a local LLM on the same device as the voice pipeline reduces performance and increases latency; for high concurrency plus large models, choose a higher compute tier.


Core Advantages

  • Wake & Commands → Wake frontend, ~$10 all-in-one
  • Best-value standalone → RK series: multilingual dialogue + local LLM, single-channel, simulated voice
  • Pro-tier natural voice → J series: J3011 offers human-like voice, single-channel; J4012 adds local LLM & 2–3 channels
  • High concurrency + advanced LLM → J5012 flagship, 3+ channels, full pipeline on one device
ProductTypeChipPickup
Range
Coverage
Angle
Built-in
Amp
Core Algorithms
reSpeaker LiteLinear
2-Mic
XMOS XU3163m180°5WAEC · DoA
reSpeaker XVF3800Circular
4-Mic
XMOS XVF38005m360°5WAEC · DoA · Multi-beamforming
reSpeaker Flex Circular-4Circular
4-Mic
XMOS XVF38005m360°10WAEC · DoA · Multi-beamforming
reSpeaker Flex Linear-4Linear
4-Mic
XMOS XVF38005m180°10WAEC · DoA · Multi-beamforming

Three Core Advantages of the reSpeaker Series


Core Advantages

  • ① Superior Hardware Audio Pickup Hardware architecture purpose-built for embedded scenarios physically isolates noise interference. Combined with array layout for DOA sound-source localization, pickup performance is notably ahead of comparable products.
  • ② On-Board AI Acoustic Algorithms XMOS chip runs AEC echo cancellation, noise reduction, and beamforming on-board in real time. Clean audio is output directly from the frontend, reducing recognition errors at the backend.
  • ③ Open Ecosystem Firmware and SDK are open to developers, enabling independent parameter tuning without relying on Seeed for secondary development. Compatible with XIAO ESP32S3, Raspberry Pi, Jetson, and all USB / I²S platforms for flexible integration.

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On-Device Voice AI | Offline Assistant with Edge LLM