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This tutorial shows how to use Julius engine with SIGVerse for speech recognition.

Overview

The Speech recognition Service consists in two parallel processes :

  • The Julius Speech recognition process Julius.exe which is used to recognize speech from a microphone, to convert it to text and to publish it in a shared memory.
  • The SIGService Process Takeit.sig which reads recognized speech from shared memory and sends it to the controller.

JuliusOverview.PNG

Speach recognition plug in

Configuration

You need to run services as an administrator, go to Speech recognition Service directory , you will find 2 files: takeIt.sig and julius.exe, by right click on these files, go to properties -> Compatibility -> Privilege level and check the box "Run this program as an administrator".

To start the service, add the takeIt.sig file to SIGViewer services, it will automatically launch the julius.exe process.

Ps: Don't forget to configure the microphone before.

Speech recognition grammar

Building grammar

Use Language Model file which contains a large list of words and their probability of occurrence in a given sequence or grammar file which contains much smaller sets of predefined combinations of words. Each word in grammar file has an associated list of phonemes (which correspond to the distinct sounds that makes a word). Acoustic model is associated to grammar, it contain a statistical representation of each sound that makes each word, each sound corresponds to a phoneme.

Recognition grammar is separated into two files:

• the ".grammar" file which defines a set of rules governing the words that Julius is expected to recognize; rather than listing out each word in the .grammar file, the Julius grammar file uses "Word Categories" - which is the name for a list of words to be recognized (which are defined in a separate ".voca" file);

• the ".voca" file which defines the actual "Word Candidates" in each Word Category and their pronunciation information.

  • User has to use grammar generator to create new grammars
  • Please refer to this tutorial for more information about grammar <link> .

You can use the file VoxForgeDict that contains the dictionary, it is located in:

PATH-TO-SERVICE\SIGVerseGrammar\VoxForgeDict

Compiling grammar

The .grammar and .voca files need to be compiled into ".dfa" and ".dict" files so that Julius can use them. This is done using "mkdfa.pl" grammar compiler. The .grammar and .voca files need to have the same file prefix, and this prefix is then specified to the mkdfa.pl script.

  • Compile your files (sample.grammar and sample.voca) as follows:
  • Command to execute:
 PATH-TO-SERVICE/mkdfa.pl .\grammar\simple

This will generate the expected grammar

GrammarGen.PNG

  • It generates sample.dfa and sample.term files which contain automation information, and sample.dict files which contain word dictionary information. Now user can perform recognition on the new defined grammar.

Controller

The controller receives messages from the SIGVerse service and convert them to commands.

voiceRecognition.cpp:

#include "Controller.h"
#include "Logger.h"
#include <unistd.h>
#include "ControllerEvent.h"
#include <sstream>
class voiceRecognition : public Controller
{
public:
 void onInit(InitEvent &evt);
 double onAction(ActionEvent &evt);
 void onRecvMsg(RecvMsgEvent &evt);
public:
RobotObj *my;
 double velocity;
 int i;
 double direction1;
 double direction2;
int j;
double Weel_one;
double Weel_two;
};
void voiceRecognition::onInit(InitEvent &evt)
{
Weel_one = 0.0;
Weel_two = 0.0;
my = this->getRobotObj(this->myname());
my->setWheel(10.0, 10.0);
}
double voiceRecognition::onAction(ActionEvent &evt)
{
my->setWheelVelocity(Weel_one,Weel_two);
return 0.01;
}
void voiceRecognition::onRecvMsg(RecvMsgEvent &evt)
{
 std::string sender = evt.getSender();
 std::string msg = evt.getMsg();
 LOG_MSG(("message : %s", msg.c_str()));
if(strcmp("moveforward",msg.c_str())==0)
{
Weel_one = 3.0;
Weel_two = 3.0;
}
   else if(strcmp("back",msg.c_str())==0)
   {
Weel_one = -3.0;
Weel_two = -3.0;
}
     else if(strcmp("turnleft",msg.c_str())==0)
 {
Weel_one = 0.78;
Weel_two = -0.78;
  }
  else if(strcmp("turnright",msg.c_str())==0)
    {
Weel_one = -0.78;
Weel_two = 0.78;
   }
}
extern "C"  Controller * createController ()
{
  return new voiceRecognition;
}

If you want to Enable/disable the speech recognition service to avoid some conflicts, you need to send these messages to the service when needed:

Enable service:

 sendMsg(“VoiceReco_Service”,”Start_Recognition”)

Disable service:

 sendMsg(“VoiceReco_Service”,”Stop_Recognition”) 

World file

VoiceRecognition.xml:

<?xml version="1.0" encoding="utf-8"?>
<world name="myworld1">
 <gravity x="0.0" y="-980.7" z="0.0"/>
 <instanciate class="WheelRobot-nii-v1.xml" type="Robot">
   <set-attr-value name="name" value="robot_000"/>
   <set-attr-value name="language" value="c++"/>
   <set-attr-value name="implementation"
                   value="./voiceRecognition.so"/>
   <set-attr-value name="dynamics" value="false"/>
   <set-attr-value name="x" value="-100.0"/>
   <set-attr-value name="y" value="30.0"/>
   <set-attr-value name="z" value="-130.0"/>
   <set-attr-value name="collision" value="true"/>
   <!--stereo camera right-->
   <camera id="1"
           link="REYE_LINK"
           direction="0.0 -1.0 1.0"
           position="0.0 0.0 3.0"/>
   <!--stereo camera left-->
   <camera id="2"
           link="LEYE_LINK"
           direction="0.0 -1.0 1.0"
           position="0.0 0.0 3.0"/>
   <!--distance sensor-->
   <camera id="3"
           link="WAIST_LINK0"
           direction="0.0 0.0 1.0"
           position="0.0 -5.0 20.0"/>
   <!--monitoring camera-->
   <camera id="4"
           link="WAIST_LINK2"
           direction="0 0 1"
           quaternion="0.0 0.0 -0.966 0.259"
           position="0.0 40.0 120.0"/>
 </instanciate>
</world>

Running the service

Here are steps to follow to run the project:

  • First, you need to run the controller, go to the controller directory and run execute this line:
$ sigserver.sh -w ./VoiceRecognition.xml
  • After that, you have to run the SIGViewer.
  • Then, run the takeIt.exe service for speech recognition, you need to configure the microphone first.

To make the robot moving, the allowed voice commands are : move forward, move backward, turn left and turn right.

Speech Recognition Service Source code

Julius process

The Julius project can be downloaded from the official website, the version used is 4.1.5, it was integrated with the SIGVerse speech recognition service. The main is to retrieve the recognized speech as text and send it to the SIGVerse service, to do so, the "output_stdout.cpp" file which aims to print the recognized text was modified to allow the communication with the SIGVerse service using the windows shared memroy.

It is located in : path_to_julius_service\julius\output_stdout.cpp

Source code explanation

Below is the main lines for retriving the recognized text and publishing the on the shared memory:

output_stdout.cpp file:

Create a new file mapping object, and initialize a buffer.

This part of code allows to retrieve the recognized text and print it in the shared memory.

SIGService process

This is the SIGVerse service for speech recognition, its aim is to retrieve the recognized speech from the windows shared memory published by Julius proces and to send it to the SIGVerse controller to control the robot.

Source code explanation

recognition.cpp:

Initialize a TCHAR variable with the name of the mapping object

Start the julius service.

Create and initialize the file mapping object.

Create a buffer.

std::string send_msg =(std::string) pBuf;
this->sendMsg("robot_000",send_msg.c_str());

Send the recognized text to the controller.

Enable/Disable the recognition when needed.

Compiling the project

You first need to download the whole project from the GIT repository.

Go to "SIGVerseJulius\msvc" and open the VS 2008 project. You also need to include SIGVerse libraries.

In the solution explorer window, 4 projects are listed, you have to compile them in the following order:

1) libsent
2) libjulius
3) julius
4) takeIt

Downloading the project

To download the project from GIT repository, use the following link:

https://github.com/SIGVerse/samples/tree/master/SpeechRecognition

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Last-modified: 2014-10-25 (Sat) 21:52:11 (1450d)