public Matrix createCrossComparison(String trainingSample, String verifySample)
throws IOException, ClassNotFoundException {
String dir =
"/Users/thomaskaiser/Documents/MCM/MC480_Project_I/SVN/trunk/Implementation/ProjectFiles/mobile phone folder structure";
HashMap<String, String> sampleDirectories = readSampleDirectories(dir);
Set<String> keySet = sampleDirectories.keySet();
int count = keySet.size();
Matrix results = new Matrix(count, count);
List<String> speakerIdList = new ArrayList<String>(keySet);
double[][][] trainingMfccs = new double[count][][];
double[][][] verifyMfccs = new double[count][][];
Codebook[] codebooks = new Codebook[count];
for (int i = 0; i < count; i++) {
String currentDir = sampleDirectories.get(speakerIdList.get(i));
double[] samples = readSamples(currentDir, trainingSample);
trainingMfccs[i] = calculateMFCCs(samples);
codebooks[i] = trainCodebook(trainingMfccs[i]);
writeCodebook(currentDir, codebooks[i]);
samples = readSamples(currentDir, verifySample);
verifyMfccs[i] = calculateMFCCs(samples);
// codebooks[i] = readCodebook(currentDir);
}
double distortion = 0;
double sumDistortion = 0;
double avgDistortion = 0;
for (int i = 0; i < count; i++) {
double minDist = Double.MAX_VALUE;
int minDistIndex = -1;
for (int j = 0; j < count; j++) {
distortion = ClusterUtil.calculateAverageDistortion(verifyMfccs[i], codebooks[j]);
sumDistortion += distortion;
results.set(i, j, distortion);
if (distortion < minDist) {
minDistIndex = j;
minDist = distortion;
}
}
avgDistortion = sumDistortion / count;
sumDistortion = 0;
Log.d(
"Min. Distortion for %d is: %7.2f. Avg. Distortion to all: %7.2f. Ratio: %5.3f",
i, minDist, avgDistortion, (minDist / avgDistortion));
}
return results;
}
public void testSampleCrossComparison(String sampleFileName) throws IOException {
String dir =
"/Users/thomaskaiser/Documents/MCM/MC480_Project_I/SVN/trunk/Implementation/ProjectFiles/mobile phone folder structure";
HashMap<String, String> sampleDirectories = readSampleDirectories(dir);
Set<String> keySet = sampleDirectories.keySet();
int count = keySet.size();
Matrix results = new Matrix(count, count);
for (String speakerId : keySet) {
double[] sampleValues = readSamples(sampleDirectories.get(speakerId), sampleFileName);
double[][] mfcc = calculateMFCCs(sampleValues);
String minDistanceSampleId = null;
double minAverageDistortion = Double.MAX_VALUE;
double sumDistortion = 0;
double avgDistortion = 0;
int codebookCount = keySet.size();
for (String sampleId : keySet) {
Codebook cb = readCodebook(sampleDirectories.get(sampleId));
if (cb != null) {
double averageDistortion = ClusterUtil.calculateAverageDistortion(mfcc, cb);
sumDistortion += averageDistortion;
Log.d("Calculated avg distortion=%f", averageDistortion);
if (averageDistortion < minAverageDistortion) {
minAverageDistortion = averageDistortion;
minDistanceSampleId = sampleId;
}
}
}
avgDistortion = (sumDistortion) / (codebookCount);
Log.d("******\nFound minimum codebook distance for speaker: %s", speakerId);
Log.d(
"Least codebook distance for: %s\n Distance: %.2f\n Average Distance %.2f",
minDistanceSampleId, minAverageDistortion, avgDistortion);
}
}
