public void convert()
{
for (int NTrainingSpeakers = 1; NTrainingSpeakers < MSpeakers; NTrainingSpeakers++)
{
for (int NTrainingSamplesPerSpeaker = startingNumberOfSamples; NTrainingSamplesPerSpeaker <= MSample; NTrainingSamplesPerSpeaker++)
{
setUpTrainingSet(NTrainingSpeakers, NTrainingSamplesPerSpeaker);
foreach (List<int> speakerList in trainingSet[0])
{
foreach (List<int> sampleList in trainingSet[1])
{
List<int> trueSampleList = new List<int>();
foreach (int index in sampleList)
{
trueSampleList.Add(index + 1);
}
gc = new GrammarCreator(directory, gr.getFileName(speakerList, trueSampleList), "allcombinations");
Dictionary<string, List<string>> pronunciations = gr.output(speakerList, trueSampleList);
gc.boundgr(true);
gc.boundrule(true, gc.grammarRuleName);
foreach (string wordType in pronunciations.Keys)
{
for (int i = 0; i < pronunciations[wordType].Count; i++)
{
gc.LogGrammar("<item><token sapi:pron=\"" + pronunciations[wordType][i] + "\">" + wordType + "_" + i + "</token></item>");
}
}
gc.boundrule(false, "");
gc.boundgr(false);
}
}
}
}
}
static void Main(string[] args)
{
// words to be tested
List<int> wordsToBeTested = new List<int>();
for(int i = 1; i <= 100; i++)
wordsToBeTested.Add(i);
//wordsToBeTested.Add(1);
// samples to be tested
List<int> samplesToBeTested = new List<int>();
samplesToBeTested.Add(1);
samplesToBeTested.Add(2);
samplesToBeTested.Add(3);
samplesToBeTested.Add(4);
samplesToBeTested.Add(5);
// audio directory
List<string> audioDirectory = new List<string>();
audioDirectory.Add("C:\\Users\\Administrator\\Documents\\Visual Studio 2008\\Projects\\cmuspeechrecognition_cmuspeechmain\\test_data\\audio\\092910_123758_Hebrew");
audioDirectory.Add("C:\\Users\\Administrator\\Documents\\Visual Studio 2008\\Projects\\cmuspeechrecognition_cmuspeechmain\\test_data\\audio\\101410_140344_Hebrew");
audioDirectory.Add("C:\\Users\\Administrator\\Documents\\Visual Studio 2008\\Projects\\cmuspeechrecognition_cmuspeechmain\\test_data\\audio\\101510_111237_Hebrew");
// audio file names
List<string> audioFileNames = new List<string>();
audioFileNames.Add("[Wed_(Sep_29_2010)_12-37-58]_4124143701_");
audioFileNames.Add("[Thu_(Oct_14_2010)_14-03-44]_4122688595_");
audioFileNames.Add("[Fri_(Oct_15_2010)_11-12-37]_4126203298_");
for (int i = 0; i < 3; i++)
{
List<int> speakersToBeTested = new List<int>();
speakersToBeTested.Add(i);
// set up data
data = new Data(audioDirectory, audioFileNames, 5, speakersToBeTested, wordsToBeTested, samplesToBeTested,
"C:\\Users\\Administrator\\Documents\\Visual Studio 2008\\Projects\\cmuspeechrecognition_cmuspeechmain\\test_data\\config_files\\config.txt.100.english");
// setup grammar
GrammarCreator gc = new GrammarCreator("C:\\Users\\Administrator\\Documents\\Visual Studio 2008\\Projects\\cmuspeechrecognition_cmuspeechmain\\test_data", "Hebrew", "allcombinations");
// setup training
TrainingAlgorithm ta = new TrainingAlgorithm(gc, data, 10, 15);
ta.LearnAllWords();
}
}
/**************************************************************************************/
/*
/* Testing algorithms
/*
/***************************************************************************************/
/// <summary>
/// Runs the testing algorithm
/// </summary>
public void testingAlgorithmDiscriminative()
{
for (int NTrainingSpeakers = 1; NTrainingSpeakers < MSpeakers; NTrainingSpeakers++)
{
for (int NTrainingSamplesPerSpeaker = startingNumberOfSamples; NTrainingSamplesPerSpeaker <= MSample; NTrainingSamplesPerSpeaker++)
{
setUpTrainingSet(NTrainingSpeakers, NTrainingSamplesPerSpeaker);
foreach (List<int> speakerList in trainingSet[0])
{
foreach (List<int> sampleList in trainingSet[1])
{
Dictionary<string, List<string>> pronunciations;
/*if (input == null)
{
pronunciations = trainAllWords(speakerList, sampleList);
}
else
{
List<int> trueSampleList = new List<int>();
foreach (int sample in sampleList)
{
trueSampleList.Add(sample + 1);
}
pronunciations = input.output(speakerList, trueSampleList);
System.Diagnostics.Debug.WriteLine(pronunciations.Count);
}*/
// set up testSpeakerSet
List<int> testSpeakerSet = new List<int>();
for (int speakerNum = 0; speakerNum < MSpeakers; speakerNum++)
{
if (!speakerList.Contains(speakerNum))
{
testSpeakerSet.Add(speakerNum);
}
}
// begin testing
foreach (int vocabSize in V)
{
foreach (int iTestSpeaker in testSpeakerSet)
{
if (input == null)
{
pronunciations = trainAllWords(speakerList, sampleList);
}
else
{
List<int> trueSampleList = new List<int>();
foreach (int sample in sampleList)
{
trueSampleList.Add(sample + 1);
}
pronunciations = input.outputDiscriminative(speakerList, trueSampleList, (iTestSpeaker+ 1));
System.Diagnostics.Debug.WriteLine(pronunciations.Count);
}
for (int iWordType = 1; iWordType <= MWordTypes; iWordType++)
{
System.Diagnostics.Debug.WriteLine("Testing: word" + iWordType);
for (int iRepeat = 1; iRepeat <= repeats; iRepeat++)
{
// create random vocab
GrammarCreator gc = new GrammarCreator(grammarDirectory, "repeat_" + grammarCounter, "allcombinations");
grammarCounter++;
gc.boundgr(true);
gc.boundrule(true, gc.grammarRuleName);
// add correct word
for (int i = 0; i < pronunciations[data.listOfWords[iWordType]].Count; i++)
{
for (int j = 0; j < MSample; j++)
{
ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, MSample * (iWordType - 1) + j, numberOfAlternates * (iWordType - 1) + i].den++;
}
gc.LogGrammar("<item><token sapi:pron=\"" + pronunciations[data.listOfWords[iWordType]][i] + "\">" + data.listOfWords[iWordType] + "_" + i + "</token></item>");
}
/*foreach (string pronun in pronunciations[data.listOfWords[iWordType]])
{
gc.LogGrammar("<item><token sapi:pron=\"" + pronun + "\">" + data.listOfWords[iWordType] + "</token></item>");
}*/
// add V - 1 random words
Random random = new Random();
List<int> wordTypesChosen = new List<int>();
wordTypesChosen.Add(iWordType);
//ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, iWordType - 1, iWordType - 1].den += MSample;
int wordCount = 1;
while (wordCount < vocabSize)
{
int randomWordType;
if (vocabSize < MWordTypes)
{
do
{
randomWordType = random.Next(1, MWordTypes + 1); // 1 to MWordTypes
} while (wordTypesChosen.Contains(randomWordType));
// add word
wordTypesChosen.Add(randomWordType);
for (int i = 0; i < pronunciations[data.listOfWords[randomWordType]].Count; i++)
{
for (int j = 0; j < MSample; j++)
{
ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, MSample * (iWordType - 1) + j, numberOfAlternates * (randomWordType - 1) + i].den++;
}
gc.LogGrammar("<item><token sapi:pron=\"" + pronunciations[data.listOfWords[randomWordType]][i] + "\">" + data.listOfWords[randomWordType] + "_" + i + "</token></item>");
}
wordCount++;
}
else
{
for (int k = 1; k <= MWordTypes; k++)
{
randomWordType = k;
// we don't add the "correct" word
if (randomWordType != iWordType)
{
wordTypesChosen.Add(randomWordType);
for (int i = 0; i < pronunciations[data.listOfWords[randomWordType]].Count; i++)
{
for (int j = 0; j < MSample; j++)
{
ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, MSample * (iWordType - 1) + j, numberOfAlternates * (randomWordType - 1) + i].den++;
}
gc.LogGrammar("<item><token sapi:pron=\"" + pronunciations[data.listOfWords[randomWordType]][i] + "\">" + data.listOfWords[randomWordType] + "_" + i + "</token></item>");
}
//System.Diagnostics.Debug.WriteLine("word chosen: " + randomWordType);
}
}
break;
}
//ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, iWordType - 1, randomWordType - 1].den+=MSample;
/*foreach (string pronun in pronunciations[data.listOfWords[randomWordType]])
{
gc.LogGrammar("<item><token sapi:pron=\"" + pronun + "\">" + data.listOfWords[randomWordType] + "</token></item>");
}*/
//wordCount++;
}
gc.boundrule(false, "");
gc.boundgr(false);
// setup recognizer
SpeechRecognitionEngine rec = new SpeechRecognitionEngine();
rec.LoadGrammar(gc.getGrammar());
// recognizing
for (int iSample = 1; iSample <= MSample; iSample++)
{
rec.SetInputToWaveFile(data.getAudioName(iTestSpeaker, iWordType, iSample));
RecognitionResult result;
try
{
result = rec.Recognize();
}
catch (Exception e)
{
System.Diagnostics.Debug.WriteLine(e.Message);
System.Diagnostics.Debug.WriteLine(data.getAudioName(iTestSpeaker, iWordType, iSample));
continue;
}
//System.Diagnostics.Debug.WriteLine("recognising");
if (result == null)
{
ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, MSample * (iWordType - 1) + iSample - 1, numberOfAlternates * MWordTypes].num++;
}
else
{
string[] word = result.Alternates[0].Words[0].Text.Split('_');
word = wordTypeResult(2, result);
//if (result.Alternates.Count > 2)
// System.Diagnostics.Debug.WriteLine("No. of results found for wordType " + iWordType + "sample " + iSample + " = " + result.Alternates[2].Confidence);
ConfusionMatrix[NTrainingSpeakers - 1, iTestSpeaker, MSample * (iWordType - 1) + iSample - 1, numberOfAlternates * (Array.IndexOf(data.listOfWords.ToArray(), word[0]) - 1) + int.Parse(word[1])].num++;
if (word[0].Equals(data.listOfWords[iWordType]))
SampleAccuracy[NTrainingSpeakers - 1, NTrainingSamplesPerSpeaker - 1, Array.IndexOf(V, vocabSize), iTestSpeaker, iWordType - 1, iSample - 1].num++;
}
/*
if (result != null && result.Alternates[0].Words[0].Text.Split('_')[0].Equals(data.listOfWords[iWordType]))
{
SampleAccuracy[NTrainingSpeakers - 1, NTrainingSamplesPerSpeaker - 1, Array.IndexOf(V, vocabSize), iTestSpeaker, iWordType - 1, iSample - 1].num++;
//System.Diagnostics.Debug.WriteLine(NTrainingSpeakers + "_" + NTrainingSamplesPerSpeaker + "_" + Array.IndexOf(V, vocabSize) + "_" + iTestSpeaker + "_" + iWordType + "_" + iSample);
}*/
SampleAccuracy[NTrainingSpeakers - 1, NTrainingSamplesPerSpeaker - 1, Array.IndexOf(V, vocabSize), iTestSpeaker, iWordType - 1, iSample - 1].den++;
}
gc.Destroy();
}
}
}
}
// end testing
}
}
}
}
}
/// <summary>
/// Given a list of speakers and the samples per speakers to train on, training is carried out to produce a List of pronunciations
/// </summary>
/// <param name="speakerList">list of speakers for training</param>
/// <param name="sampleList">list of samples for training</param>
/// <returns>List of pronunciations</returns>
private Dictionary<string, List<string>> trainAllWords(List<int> speakerList, List<int> sampleList)
{
string speaker = "speaker-";
for (int i = 0; i < speakerList.Count; i++)
{
speaker += speakerList[i].ToString()+"_";
}
string sample = "sample-";
List<int> trueSampleList = new List<int>();
trueSampleList.AddRange(sampleList);
for (int i = 0; i < trueSampleList.Count; i++)
{
trueSampleList[i]++;
sample += trueSampleList[i].ToString() + "_";
}
System.Diagnostics.Debug.WriteLine("training " + speaker + sample);
// words to be tested
List<int> wordsToBeTested = new List<int>();
for (int i = 1; i <= MWordTypes; i++)
wordsToBeTested.Add(i);
// set up data
Data tempData = new Data(data.audioDirectory, data.audioFileName, data.numberOfSamplesPerWord, speakerList, wordsToBeTested, trueSampleList,
data.wordListPath);
// setup grammar
GrammarCreator gc = new GrammarCreator(grammarDirectory, data.language + speaker + sample, "allcombinations");
// setup training
TrainingAlgorithm ta = new TrainingAlgorithm(gc, tempData, numberOfAlternates, 15);
return ta.LearnAllWords();
}
