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Amlogic A113X1 6-Mic Far-Field Devkit is Designed for Amazon Alexa

January 11th, 2018 2 comments

Allwinner unveiled their SoC-Only 3-Mic Far-Field Development Kit for Amazon AVS last week, but they are now joined by another low cost silicon vendor as Amlogic has just launched their own A113X1 far-field dev kit officially support for Amazon Alexa Voice Service (AVS).

The development kit is powered by Amlogic A113X SoC designed for such applications with “an audio pipeline that supports high fidelity audio with soft DSP algorithms for both frontend and backend processing”.

 

Amlogic A113X1 far-field devkit specifications:

  • Mainboard
    • SoC – Amlogic A113X quad core Cortex A53 processor
    • System Memory – 512MB DDR3
    • Storage – 512 MB NAND flash
    • Connectivity – SDIO WiFi/BT (AP6356S)
    • Audio
      • SPDIF_IN jack
      • LINE_IN/LINE_OUT jacks
      • 2x Audio headers (MIC_Connector & SPK_Connector)
    • USB – 1x micro USB 2.0 OTG port
    • Expansion – SPI header
    • Misc – 6x ADC Keys, IR_IN/IR_OUT, UART Interface (RS232), LEDs
    • Power Supply – 12V/2A
  • Microphone board
    • 6x digital microphones in a circular array
    • Texas Instruments PCA9557PWR IO expander
  • Speaker board
    • Texas Instruments TAS5707PHPR 20-W Open-Loop Stereo Digital Input Class-D Audio Amplifier with Speaker EQ and DRC
    • Power Supply – 12V DC barrel jack

The solution is said to run “high-performance DSP algorithms for acoustic echo cancellation, beamforming, and noise reduction”.

 

Beside the three boards of the kit (main, speaker, and microphone), you’ll also get a power supply, a serial debug adapter, and a pair of generic speakers. You’ll find more documentation, a getting started guide (with a Linux 4.9 buildroot based distribution), and a purchase link for the $250 kit on a dedicated Amazon Developer page. The kit is currently demonstrated at the Amlogic suite in the Venetian (Suite #34311) during CES 2018.

We’ll also find the kit in company of the aforementioned $129 Allwinner Amazon AVS kit, a new $1,250 “Qualcomm Smart Audio 6-Mic Development Kit for Amazon AVS”, and as well as the $299 hands-free “Synaptics AudioSmart 2-Mic Dev Kit for Amazon AVS” on the System Dev Kits section of Amazon AVS Development Kits page.

 

Amlogic Far-field Kit Accessories – Click to Enlarge

 

Thanks to Theguyuk for the tip

$129 Allwinner R18 based 3-Mic Far Field Amazon AVS Development Kit in the Works

January 4th, 2018 17 comments

Several companies are already offering development kits for Amazon AVS (Alexa Voice Service), but as we’ve seen in the past, those are rather expensive with far-field kits such starting at $349 with kits such as Synaptics AudioSmart 4-Mic Development Kit, or Intel Speech Enabling Developer Kit, and hands-free kits being barely cheaper at $299 and up.

But there will soon be a cheaper solution, as Allwinner and SinoVoIP (aka Banana Pi) are working on “SoC-Only 3-Mic Far-Field Dev Kit for Amazon AVS” that includes 3 microphones, and works without special DSP, relying instead on Allwinner R18 processor’s audio codec and capabilities.

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Allwinner SoC-Only 3-Mic Far-Field Dev Kit for Amazon AVS (aka R18-AVS-EVK) specifications:

  • SoC – Allwinner R18 quad-core Cortex-A53 processor @ 1.15GHz with Mali400MP2 GPU
  • System Memory – 1GB DDR3
  • Storage – 8GB eMMC flash
  • Video Output – HDMI
  • Audio – 6x Microphones, 2x AEC, AUX and headphone output; GMEMS voice recognition algorithm
  • Connectivity – Dual band WiFi, Bluetooth 4.0
  • USB – 1x USB type A port, 1x micro USB OTG port
  • Power Supply – 12V DC input
  • Dimensions – Mainboard: 100 x 100mm; microphone array board: 90 mm ∅

The board will support Linux operating systems at first, but Android is also being worked on. A ribbon cable is also included in the kit to connect the mic array to the main board. Now you may wonder why a 3-mic development kit comes with 6 microphones. Allwinner explains:

6 microphones are included on the board, while only three are used and qualified, providing flexibility to tune for 6/4/3/2 mic solutions and freely match with different product designs

I’m not 100% sure what that means, but I guess the kit only works for three for now, but in the future algorithms may support a combination of up to 6 microphones. We’ll have to see how the solution works compared to DSP based systems.

Allwinner R18 Block Diagram

The development kit is now found on Amazon website yet, but a page on Banana Pi website mentions they are 50 unit for pre-sale for $129 with shipping scheduled on February 5, 2018. The “Buy” link does not work yet. A few more details may be found in the product page on Allwinner website.

Amazon FreeRTOS Released for NXP, Texas Instruments, STMicro, and (soon) Microchip Microcontrollers

December 2nd, 2017 7 comments

FreeRTOS is an open source real-time operating system for microcontrollers released under an MIT license, and when it comes to adoption in embedded systems it’s right there near the top with embedded Linux according to Aspencore 2017 embedded markets study. For example, some Espressif SDKs for ESP8266 or ESP32 are based on FreeRTOS, and so is Mediatek LinkIt Development Platform for RTOS.

The recently announced Amazon FreeRTOS (a:FreeRTOS) leverages the open source operating systems, and extends it with with libraries that enable local and AWS cloud connectivity, security, and soon over-the-air updates. a:FreeRTOS is free of charge, open source, and available today.

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In order to get started, you’ll have a choice of 4 hardware platforms:

  • STMicro STM32L4 Discovery Kit IoT Node (B-L475E-IOT01A) powered by STM32L475 ARM Cortex-M4 MCU with 802.11 b/g/n WiFi, Bluetooth 4.1 LE, RF (868 / 915 MHz), and NFC connectivity, plenty of sensors

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  • Texas Instruments SimpleLink Wi-Fi CC3220SF LaunchPad development kit (CC3220SF-LAUNCHXL) with  CC3220SF single-chip WiFi microcontroller (MCU) with 1MB Flash, 256KB of RAM.

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  • Microchip Curiosity PIC32MZ EF Development Board (Amazon FreeRTOS support coming soon) powered by PIC32MZ EF MCU (415 DMIPS) with 2 MB Flash, 512 KB RAM, integrated FPU, crypto accelerator, and connectivity via an on-board 802.11 b/g/n Wi-Fi module, and two MikroBUS connector for add-on boards.

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If you don’t own any of those boards, or don’t plan to purchase one, but still would like to play with a:FreeRTOS you could run the Windows Simulator instead.

Once we’ve selected our hardware platform (or simulator), we can access Amazon FreeRTOS console to configure and download the FreeRTOS kernel and software libraries for our application.  Development of the application is done though the tools provided for the board for example TI Code Composer Studio, STM32 System Workbench, IAR Embedded Workbench, or Visual Studio Community Edition.

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Amazon FreeRTOS is free as in speech and free as in beer, with the source code and links to documentation available in Github. Amazon will make money when you utilize AWS services such as AWS IoT Core, data transfer, or AWS Greengrass. The price list of AWS services that may be charged (if enabled) while using Amazon FreeRTOS can be found here.

AWS DeepLens is a $249 Deep Learning Video Camera for Developers

November 30th, 2017 4 comments

Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models.

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AWS Deeplens specifications:

  • Camera – 4MP (1080p) camera using MJPEG, H.264 encoding
  • Video Output – micro HDMI port
  • Audio – 3.5mm audio jack, and HDMI audio
  • Connectivity – Dual band WiFi
  • USB – 2x USB 2.0 ports
  • Misc – Power button; camera, WiFi and power status LEDs; reset pinhole
  • Power Supply – TBD
  • Dimensions – 168 x 94 x 47 mm
  • Weight – 296.5 grams

The camera can not only do inference, but also train deep learning models using Amazon infrastructure. Performance wise, the camera can infer 14 images/second on AlexNet, and 5 images/second on ResNet 50 for batch size of 1.

Six projects samples are currently available: object detection, hot dog not hot dog, cat and dog,  activity detection, and face detection. Read that blog post to see how to get started.

But if you want to make your own project, a typical workflow would be as follows:

  • Train a deep learning model using Amazon SageMaker
  • Optimize the trained model to run on the AWS DeepLens edge device
  • Develop an AWS Lambda function to load the model and use to run inference on the video stream
  • Deploy the AWS Lambda function to the AWS DeepLens device using AWS Greengrass
  • Wire the edge AWS Lambda function to the cloud to send commands and receive inference output

This steps are explained in details on Amazon blog.

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Intel also published a press release explaining how they are involved in the project:

DeepLens uses Intel-optimized deep learning software tools and libraries (including the Intel Compute Library for Deep Neural Networks, Intel clDNN) to run real-time computer vision models directly on the device for reduced cost and real-time responsiveness.

Developers can start designing and creating AI and machine learning products in a matter of minutes using the preconfigured frameworks already on the device. Apache MXNet is supported today, and Tensorflow and Caffe2 will be supported in 2018’s first quarter.

AWS DeepLens can be pre-ordered today for $249 by US customers only (or those using a forwarding service) with shipping expected on April 14, 2018. Visit the product page on AWS for more details.

Amazon Fire TV Stick Basic Edition Ships to over 100 Countries for $50

November 8th, 2017 3 comments

Amazon products are usually launched in the US, and a limited number of European countries, meaning most people can’t purchase or use their devices without going through various hoops.

But the company has now launched a basic edition of their latest Fire TV stick 2016 sold in over 100 countries. Basic means it supports Amazon Alexa voice services, and you pay around $10 extra for the privilege. Apart from that it looks exactly the same.

Supported languages are still quite limited with Spanish, Brazilian Portuguese, French, Italian, German, or English, and the company mentions people will have access to videos from Amazon Prime Video with “unlimited access to critically acclaimed shows like The Tick, American Gods, and The Man in the High Castle as well as The Grand Tour Season 2″

Hardware looks the same with a quad-core processor coupled with 1 GB of memory and 8 GB of storage for apps and games. Network connectivity is achieved via  802.11ac Wi-Fi, and the stick supports 1080p HEVC streaming, as well as Dolby Audio.

Fire TV Basic Edition can be purchased for $49.99 on Amazon US (and other Amazon local websites). Visit the Amazon link, and select your country to check whether the stick can be shipped there.

So I checked to see what price I would have to pay to get such device, and total price is $84.09 including a $13.12 import fees deposit. Amazon estimates no taxes would have to be collected, but I would likely be asked to pay 7% VAT. Unless Amazon somehow bribed found an agreement with local authorities, I would also have to fly to the capital city to apply for a “broadcasting license” from a government entity (NBTC) in order for the package to go through customs. No thanks.

Via Liliputing

Categories: Android, Hardware Tags: amazon, TV box

Intel Speech Enabling Developer Kit Works with Alexa Voice Service, Raspberry Pi 3 Board

October 28th, 2017 4 comments

We’ve known Intel has been working on Quark S1000 “Sue Creek” processor for voice recognition for several months. S1000 SoC is based on two Tensilica LX6 with HiFi3 DSP, some speech recognition accelerators, and up to 8x microphones interfaces which allows it to perform speech recognition locally. The solution can also be hooked to an application processor via SPI, I2S and USB (optional) when cloud based voice recognition is needed.

Intel has recently introduced their Speech Enabling Developer Kit working with Amazon Alexa Voice Service (AVS) featuring a “dual DSP with inference engine” – which must be Quark S1000 – and an 8-mic array. The kit also includes a 40-pin cable to connect to the Raspberry Pi 3 board.

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Intel only provided basic specifications for the kit:

  • Intel’s dual DSP with inference engine
  • Intel 8-mic circular array
  • High-performance algorithms for acoustic echo cancellation, noise reduction, beamforming and custom wake word engine tuned to “Alexa”
  • 6x Washers
  • 3x 6mm screws
  • 3x 40mm female-female standoffs (x3)
  • Raspberry Pi connector cable

I could not find detailed information to get started, except for assembly guide shown in the video below. We do not that the kit will work with Amazon Alexa, and requires a few extra bits, namely a Raspberry Pi 3 board, an Ethernet cable, a HDMI cable and monitor, USB keyboard and mouse, an external speaker, a micro USB power supply (at least 5V/1A), and a micro SD card.

The video also points to Intel’s Smart Home page for more details about software, but again I could not find instructions or guide there,  except links to register to a developer workshop at Amazon Re:Invent in Las Vegas on November 30, 2017.

Intel Speech Enabling Developer Kit can be pre-ordered for $399 directly on Intel website with shipping planned for the end of November. The product is also listed on Amazon Developer page, but again with little specific information about the hardware and how to use it. One can assume the workflow should be similar to other AVS devkits.

Thanks to Mustafa for the tip.

Dragonwally is a Stereoscopic Computer Vision Mezzanine for 96Boards CE Boards

October 11th, 2017 No comments

Hardware based on 96Boards specifications may not have the number of sales as Raspberry Pi or Orange Pi boards, but there’s heavily used by Linaro member and other developer working on bleeding edge software. More and more companies are designing boards compliant with the standard, and several new mezzanine expansion boards such as Secure96, were showcased at Linaro Connect SFO 2017, and are yet to be show up on 96Boards Mezzanine page.

Another 96Boards mezzanine expansion board in development is Dragonwally, designed for stereoscopic computer vision, currently used with DragonBoard 410c board, and targetting applications such as object recognition,  people counting, access control, or driver identification and safety.

DragonWally DW0 board specifications:

  • MIPI DSI interface with high speed connector
  • 2x 5MP cameras
  • 1x USB port
  • 96Boards CE compliant

The two Brazilian developers working on the project interfaced it with DragonBoard 410c running Linaro Debian, and using OpenCV and Python for computer vision development. To demonstrate the capability of the board, they added a touchscreen display for a demo leveraging Amazon Rekognition API for face recognition and camera distance estimation.

DragonWally board does not seem available yet, nor the source code for the demo above. If you’d like more information, visit DragonWally website, or join 96Boards OpenHours #74 tomorrow.

NComputing RX300 Thin Client Review – Part 2: Hardware Setup, Windows Server 2016

October 8th, 2017 8 comments

Ncomputing RX300 is a thin client based on Raspberry Pi 3 board, allowing to run Windows operating systems on a powerful server with the Raspberry Pi 3 handling the display, audio, and keyboard/mouse inputs.

The company sent me a sample for review, and I checked out the hardware and accessories in the first part entitled “NComputing RX300 Thin Client Review – Part 1: Unboxing and Teardown“, so in the post I’ve started the thin client, and connected it to vSpace Pro server.

Hardware Setup

RX300 uses the same peripherals as any mini PC, so I connected USB keyboard and mouse, an Ethernet cable (WiFi is also possible), and the power adapter. You could also connect other devices, and I added a USB flash drive which, as we’ll see later, will be properly recognized by the server. I was also sent a USB to VGA adapter that you can connect to the remaining USB port to add a secondary display, but it would never work with through my TV, maybe because VGA is limited to 1600×1050, and the resolution confused the adapter.

Server Options

You’ll also need to setup a server, and you have two main option here:

  • Download vSpace Pro 10 to install and manage a self-hosted server. I did not do this in this review, because my main PC is running Ubuntu 16.04, and the program only support Windows operating systems, and server virtualization infrastructure solutions from VMWare, Citrix and Microsoft.
  • So instead I used a vSpace Pro server hosted in Singapore using AWS (Amazon Web Services) with a demo account prepared by the company for the review

If you’re interested in the first solution, you may want to read to Quick Installation Guide to find out more.

Ncomputing RX300 and Windows Server 2016 AWS instance

Once the thin clients are installed, and the server is configured, you can start your RX300 devices. About an animated boot logo, you should soon (around 15 to 20 seconds total boot) time see vSpace Pro client interface as shown below. Please ignore the vertical lines in the photos and video below, it’s just a problem with my TV.
You’ll see two sections with a list of auto-detected servers if you have setup any local vSpace Pro 10 machine, and/or server groups with other vSpace Pro servers. I’m located in the north of Thailand, and Thailand->Thailand was already setup, so I had nothing to do except click on Connect, and within a few short second, I was asked to login into Windows.

I typed the credentials provided by the demo, and I ended up in Windows right away, and could use it normally. A few times later however, I was automatically disconnected during the login process: I would type the user name and password to login, Windows desktop will appear, only go to back to vSpace Pro client interface. Trying again once or twice usually did the trick.

As soon as I entered into the server, I wanted to find out what kind of hardware the virtual machine was running on. Intel Xeon CPU E5-2676 v3 @ 2.40 GHz running Windows Server 2016 64-bit with 4 GB RAM, and a 39.9 GB Windows partition.

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Quite a powerful machine so we should expect good performance that may be affected by the Internet connection between my ISP’s modem router and the server. You’ll also notice “Ubuntu 16.10” D: drive. That’s my own flash drive connected to one of the USB port of the Raspberry Pi 3 board.

The company had install several programs such as Chrome and LibreOffice, as well as demo files.  I also tried to install my own program (Gimp), and I could do that, and persistent storage mean even after I disconnect the client, or reboot the server, my programs and files were still present in the system.

So I went on to use it like I would for a desktop machine in a business setting, browsing the web, and loading multiple programs.

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More specifically, I ran the following tests:

  • Launching Chrome, LibreOffice Calc (excel spreadsheet), LibreOffice Impress (powerpoint presentation), LibreOffice Writer (word doc), and Gimp in succession to demonstrate the speed to launch apps
  • Multi-tab browsing in Chrome and Octane 2.0 benchmarks
  • Playing 1080p YouTube video in embedded and full screen modes
  • Playing local 1080p video with VLC

Overall the performance is impressive for a remote system, and in many cases, it’s hard to know we are not using a “normal” computer. The fonts may not be as sharp as on a normal PC, but it’s hardly noticeable, and the screen updates while scrolling up or down web pages are slower than on my main computer. However, I did not feel either issues were a big problem, and they will likely depend on your network performance, in my case “low to moderate”. It feels much better than the few times I used VNC in the past.

The first time however, YouTube video playback was very choppy, but then I saw Chrome complaining about “vCAST feature not available”. vCast streaming technology is a premium feature allowing you to watch videos smoothly on thin clients. After the company enable vCAST in the server, I could streaming 1080p YouTube videos, and play local video in VLC smoothly.

You can watch the video below to have an idea of the performance, and a look at the client settings.

Once you are done, you can click on the power icon and select Disconnect to go back to vSpace Pro client user interface.

vSpace Pro client configuration options and Going back to Raspbian

If you’ve watched the video above, you’ll know that the gear icon on the bottom right brings use to the configuration menu.

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The menu has eight sub-menus:

  • General to select between Thin client mode and Raspbian Desktop mode
  • Connections to select servers manually or automatically
  • Server Groups to manage servers
  • Kiosk Mode to automatically login and/or launch a program when connecting to the vSpace server
  • Display to change HDMI resolution, or manage dual display setups.
  • Audio to select audio output and input priority
  • Network to configure Ethernet or WiFi
  • Support for firmware update option
  • About with some information about the thin client.

I tried the Raspbian desktop mode, and sure enough it will be into Raspbian, and you could potentially use it as a normal Raspberry Pi 3 board too.

Once you’ve selected this mode, it will boot to Raspbian by default. If you want to use it as a thin client again, the Switch to Thin Client Mode icon will reboot RX300 to vSpace client user interface.

Recycling older Windows computer with vSpace Pro Client

If your organization owns some older Windows PCs or laptops that lack the performance or memory to run recent programs, you could download vSpace Pro client for Windows to put them to good use. Just to the the Software Downloads page, register or/and login, and select vSpace Pro Client for WIndows 7, 8.1 or 10 as needed. Linux clients are not available for download.

You could then have a “fleet” a thin clients mixing older hardware and NComputing RX300. You’d have to consider electricity charges while calculating your TCO, as RX300 only consumes around 3.0 to 3.4 Watts, and older hardware may consume much more than that.

The Costs

Larger organizations should probably contact the company to find out the best way to match their requirements. But if you have smaller needs, or just want to evaluate the system, you could purchase Ncomputing RX300 for $99 MSRP with a 1-year license, or $174.99 with a 3-year license. I understand vCAST streaming is included for free for 6 months, but after you’d have to pay extra for the feature. What I could not find is public pricing for the various licenses. The company however has a cost calculator allowing you to check how much you’d save with thin clients compared to having PCs, but again premium features license costs such as vCAST or dual display are not included. You’d also have to consider Windows server license requirements.