Add files via upload

mp32wav.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+#Script: mp32wav script (requires mpg123 package)
+#Purpose: Loops through a path and convert all the mp3s to wavs
+#
+#usage: mp32wav [Path]
+
+count=0
+
+if [ -n "$1" ]; then
+   cd "$1"
+   ls
+   for file in *.mp3
+	do
+	let "count += 1"
+          echo "$1/$file" > sedEdit
+          name =`echo "$file" | cut -d'.' -f1`
+          mpg123 -w ./waves/${file}.wav $file
+	done
+fi
+echo "$count mp3s found and converted to wavs... [Baileysoft 2005]"
+rm sedEdit
+exit 0

svm_audio.py

@@ -6,7 +6,7 @@
 from sklearn.metrics import accuracy_score, precision_score, recall_score
 import numpy as np
 from csv import reader
-from sklearn.manifold.t_sne import TSNE
+#from sklearn.manifold.t_sne import TSNE
 
 def load_csv(filename):
     file = open(filename, "rt")
@@ -66,17 +66,17 @@ def SVM(train_data, train_labels, test_data, test_labels):
     metrics.append(SVM(train_data, train_labels, test_data, test_labels))
     fold += 1
 
-    accuracy = 0.00
-    precision = 0.00
-    recall = 0.00
-    fi = 0.00
-    for i in metrics:
+accuracy = 0.00
+precision = 0.00
+recall = 0.00
+fi = 0.00
+for i in metrics:
         accuracy += i[0]
         precision += i[1]
         recall += i[2]
         fi += i[3]
-    accuracy = accuracy/5.0
-    precision = precision/5.0
-    recall = recall/5.0
-    fi = fi/5.0
-    print (accuracy),(","),(precision),(", "),(recall),(", "),(fi)
+accuracy = accuracy/5.0
+precision = precision/5.0
+recall = recall/5.0
+fi = fi/5.0
+print (accuracy),(","),(precision),(", "),(recall),(", "),(fi)