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Yihui Xiong edited this page Feb 8, 2017 · 24 revisions

Welcome to ReSpeaker OLD wiki!

The latest document is at https://github.com/respeaker/get_started_with_respeaker

##Respeaker Core Hardware top view bottom view ###Features

  • AI7688 WiFi Module
    • Embedded MIPS24KEc(575/580 MHz) with 64KB I-Cache and 32KB D-Cache
    • 1T1R 2.4GHz with 150 Mbps PHY data rate
    • Legacy 802.11b/g and HT 802.11n modes
    • 20/40 MHz channel bandwidth
    • 802.11v
    • x1 USB 2.0 Host
    • SD-XC
    • I2C,GPIO
    • OpenWrt 3.10
    • 3 User buttons
  • LPC11U35 coprocessor
    • USB CDC virtual COM port for ssh
    • 4 touch sensors
    • 12 RGB LEDs control
    • 4 GPIOs with Analog input capability
  • Codec WM8960
    • DAC SNR 98dB (‘A’ weighted), THD -84dB at 48kHz, 3.3V
    • ADC SNR 94dB (‘A’ weighted), THD -82dB at 48kHz, 3.3V
    • Stereo Class D Speaker Driver • 0.1% THD with 1W per channel into 8Ω BTL speakers • 70dB PSRR @217Hz • 87% efficiency (1W output)
    • On-chip Headphone Driver • 40mW output power into 16Ω at 3.3V • THD -75dB at 20mW, SNR 90dB with 16Ω load
  • On-chip PLL provides flexible clocking scheme
  • Sample rates: 8, 11.025, 12, 16, 22.05, 24, 32, 44.1, 48 KHz

###Schematic Respeaker Core v1.0 alpha1 sch ###Component Layout Top Layer

Bottom Layer ##Respeaker Microphone Array Hardware Top View ###Description Respeaker Microphone Array is an expansion board for Repeaker which is defined for helping people who want to create themselves’ voice assistant and speaker system. It helps the Respeaker recognize people’s voice when playing music or the user is far away from Respeaker. ###Features

  • Microcontroller with 16 cores inside:
    • 16 real-time logical cores on 2 xCore tiles.
    • Cores share up to 2000 MIPS in dual issue mode.
    • 512KB internal single-cycle SRAM and 2MB built-in flash.
    • 16KB internal OTP (max 8KB per tile),
    • USB PHY, fully compliant with USB 2.0 specification.
    • Programmable I/O.
    • Supply DFU Mode.
  • 7 Digital Microphones:
    • far field voice recognition or sound localization usefulness.
    • ST MP34DT01-M.
    • -26 dBFS sensitivity.
    • 120 dBSPL acoustic overload point.
    • 61 dB signal-to-noise ratio.
    • Omnidirectional sensitivity.
    • PDM output.
  • 12 RGB LEDs:
    • 256 levels brightness.
    • 800kHz line data transmission.
  • Audio output:
    • On board 3.5mm Aux output.
    • Cirrus DAC CS43L32.
    • 24 or 16bit 16kHz stereo output.
    • 88 mW Power Into Stereo 16 Ω @ 2.5 V.
  • Clock Sync:
    • On board PLL.
    • Programmable sample clock for DAC,MIC. (Disable if DSP is used in XVSM-2000).
  • Power supply:
    • 5V supply from Micro USB or expansion header.
  • Size:
    • Diameter 70mm.
  • Weight:
    • 15.25g

Serial console

Connect to the Internet

  • Connect your smart phone/laptop to a Wi-Fi named LinkIt_Smart _xxxxxx and visit 192.168.100.1. After setting a password of respeaker and logining in, you need to select station mode, select a Wi-Fi network and enter the password as the following picture.

Station mode setting.jpg

Record & play

arecord -M -f S16_LE -r 16000 -c 1 --buffer-size=204800 -v /tmp/sample.wav   # record audio with 16000 sample rate, 16 bit width, 1 channel
aplay -M /tmp/sample.wav --buffer-size=204800 -v  # play wav audio
madplay music.mp3         # play mp3 audio

Play music with Airplay/DLNA

  • With Airplay/DLNA, you can stream music to respeaker.
  • To use Airplay/DLNA, you need to connect respeaker and your smart phone to the same Wi-Fi network.

###Use Airplay

  • On your iOS device, swipe up from the bottom of your screen to open Control Center.
  • Tap AirPlay.
  • Select "Shairport Sync on mylinkit", and play music on your iOS device.

  • Connect your headphone to respeaker, then you can enjoy the music now.

##Speech to text

  • This is a python example to use Microsoft cognitive services, you can copy it to respeaker.

$ git clone https://github.com/respeaker/microsoft_cognitive_services.git

  • Get a API key from Microsoft and add it to those scripts.
  • Install required package.

$ pip install monotonic

  • Read audio from microphone.

$ python bing_stt_with_vad.py

  • Recognize audio from file (16000 sample rate, 1 channel).

$ python bing_recognizer.py

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