Difference between revisions of "ECE597 Project NodeRed Voice"
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# Follow the directions [http://www.chromium.org/developers/how-tos/api-keys here] to get API public key for the jasper. | # Follow the directions [http://www.chromium.org/developers/how-tos/api-keys here] to get API public key for the jasper. | ||
− | # From the jasper directory navigate to clients directory and run | + | # From the jasper directory navigate to clients directory and run ''python populate.py'' |
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# Provide all the information and when prompted to enter STT enter 'google' and then enter your API key when asked. | # Provide all the information and when prompted to enter STT enter 'google' and then enter your API key when asked. | ||
# Check that everything is good to go by running jasper. It is common to have a few errors during the first startup but don't panic, as there is a very helpful [https://groups.google.com/forum/#!forum/jasper-support-forum Google Group] and [http://jasperproject.github.io/documentation/faq/ FAQ] maintained by Jasper authors. | # Check that everything is good to go by running jasper. It is common to have a few errors during the first startup but don't panic, as there is a very helpful [https://groups.google.com/forum/#!forum/jasper-support-forum Google Group] and [http://jasperproject.github.io/documentation/faq/ FAQ] maintained by Jasper authors. |
Revision as of 12:35, 13 November 2014
Embedded Linux Class by Mark A. Yoder
Team members: Dmitry , Matt Olson
Contents
Grading Template
I'm using the following template to grade. Each slot is 10 points. 0 = Missing, 5=OK, 10=Wow!
00 Executive Summary 00 Installation Instructions 00 User Instructions 00 Highlights 00 Theory of Operation 00 Work Breakdown 00 Future Work 00 Conclusions 00 Demo 00 Late Comments: I'm looking forward to seeing this. Score: 10/100
(Inline Comment)
Executive Summary
Our project has branched out along several paths since it's inception. The goal was to create a personal assistant that could listen to commands, talk back, and perform them. For modularity, our original goal was to use IBM's Node Red to accomplish this. However, Node Red is not designed for the complicated and workflows that we needed, and extensions were not scale-able. In this document we are going to describe three things.
- A simple node red speech recognition and synthesis system
- Using the open source jasper project on Raspberry Pi
- Using the open source Jasper project on Beaglebone Black
The simple node red speech synthesis will essentially listen to the user, and the repeat back what is said. Currently the speech synthesis is working, and we are trying to integrate pocket sphinx for the speech recognition.
Jasper was developed with the Raspberry Pi, and as a result has a very simple set up procedure. Our goal is too use this platform to begin developing modules. We currently have working versions of jasper installed and have 2 modules developed.
There are no reliable installation instructions for setting up Jasper on the Beaglebone black. We have done the research, and are hoping to be able to provide concise installation instructions and port over our work.
Packaging
Jerry Talyor of Mansfield, IN is going to make a fantastic wooden laser cut and laser engraved box for us.
Installation Instructions
List of required hardware
Raspberry Pi | Beaglebone Black |
---|---|
USB mic, power supply, Edimax USB wi-fi, speakers | USB audiocard, USB/Audio-In mic, speakers |
Network |
- Note: Internet connectivity is an important part of the project as we are using the Google Speech API for voice recognition in the current revision.
Setting up Network on RPi
There are two options for the internet access: wired connection and wi-fi connection. Both are very easy to manage with wicd connection manager with wicd-curses user interface.
To get wicd installed, plug the ethernet cord (assuming the initial raspbian installation it should work right out of the box) and then run:
sudo apt-get update sudo apt-get install wicd sudo apt-get install wicd-curses
Alternatively /etc/network/interfaces file should be edited to include all of the following:
auto lo iface lo inet loopback iface eth0 inet dhcp allow-hotplug wlan0 auto wlan0 iface wlan0 inet dhcp wpa-ssid "ssid" wpa-psk "password"
This also allows auto-connect to a wireless network specified on a startup.
Setting up Network on Beaglebone
Being processed.
Installing Jasper on raspberry Pi
Follow the instructions provided on the documentation page to install JASPER http://jasperproject.github.io/documentation/software/
The modules we have implemented use the python RPI.gpio library, run the following commands to install it
sudo apt-get update sudo apt-get install python-dev sudo apt-get install python-rpi.gpio
Installing our custom Modules to demonstrate Jasper
git clone https://github.com/dmitryvv/woodoo cd woodoo chmod +x install_modules_RPi.sh ./install_modules_RPi.sh
By default Jasper uses pocketsphinx as a voice recognition platform and it was found to produce a low quality recognition so we decided to move to Google Speech.
- Follow the directions here to get API public key for the jasper.
- From the jasper directory navigate to clients directory and run python populate.py
- Provide all the information and when prompted to enter STT enter 'google' and then enter your API key when asked.
- Check that everything is good to go by running jasper. It is common to have a few errors during the first startup but don't panic, as there is a very helpful Google Group and FAQ maintained by Jasper authors.
Installing Jaser on Beaglebone Black
Being processed
User Instructions
To start jasper, navigate to the jasper directory and run the following command
python jasper.py
Jasper will initialize everything, and if everything is connected properly, should prompt you for a command. The typical use case is to say Jasper for it to begin listening, wait for a high pitched beep, say your command, and then wait for another lower pitched beep for a confirmation.
You: Jasper Jasper: *BEEP* You: What time is it. Jasper: *BEEP* Jasper: It's currently now.
Highlights
Here is where you brag about what your project can do.
Include a YouTube demo.
Theory of Operation
Our project uses the opensource Jasper project as it's backbone. The system is constantly listening to it's surroundings, and when it finds a discrete sound block sends it to the google voice API for analysis. Google voice returns text blocks of what it thought the sound click was of. Jasper then runs it across modules looking for a hit, and then executes a command if it finds one.
Completed Tasks
Matt Olson
- Node Red Installed - 10/20/2014
- Wi-fi dongle working - 10/22/2014
- Created Module for Jasper - 10/28/2014
- Created install script for installing modules on RPi - 11/12/2014
Dmitry Votinstev
- Speech recognition software installed - 10/20/2014
- Sound recording/payback with arecord aplay works 10/22/2014
- Ported Jasper to Work on the Google voice API 11/12/2014
Tasks Remaining
- Develop Additional testing modules - Matt, Dmitry
- Get Jasper working on BBB - Matt, Dmitry
Future Work
Suggest addition things that could be done with this project.
Conclusions
Node Red does not provide a very good architecture for acting as a speech recognition system and dispatcher, which resulted in our choice to investigate other options.
Embedded Linux Class by Mark A. Yoder