examples unix version

mitll · Apr 21, 2017 · 35a3fdc · 35a3fdc
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diff --git a/examples/example_gsv.py b/examples/example_gsv.py
@@ -1,42 +1,42 @@
-#!/usr/bin/env python
-
-import json
-
-from pyslgr.GMMModel import GMMSAD
-from pyslgr.GSV import GSV
-from pyslgr.LLSignal import LLSignal
-from pyslgr.MFCCFeatures import MFCCFeatures
-from pyslgr.FeatPipe import FeatPipe
-from pyslgr.sad import XtalkSAD
-
-if __name__ == "__main__":
-
-    # Load example signal
-    fn = 'signals/example.sph'
-    x = LLSignal()
-    x.load_sph(fn, 0)
-
-    # Initialize feature pipe
-    mfcc_pipe_fn = "config/sid_mfcc+gmmsad_pipe.json"
-    with open(mfcc_pipe_fn, 'r') as fp:
-        pipe_config = json.load(fp)
-    fpipe = FeatPipe(pipe_config, MFCCFeatures, GMMSAD)
-
-    # Get MFCCFeatures
-    f = fpipe.process(x)
-
-    # Info
-    print 'Number of output features: {}'.format(f.num_outfeat())
-    # f.save_raw('tmp/gsv_feat.dat')
-
-    # Load in and create GSV
-    with open('config/gsv.json', 'r') as fp:
-        config = json.load(fp)
-    gsv = GSV(config)
-
-    # Now compute a GSV expansion
-    v = gsv.process(f)
-    print 'A few elements of GSV expansion: {}'.format(v[0:10])
-    print 'GSV expansion dimension = {}'.format(len(v))
-
+#!/usr/bin/env python
+
+import json
+
+from pyslgr.GMMModel import GMMSAD
+from pyslgr.GSV import GSV
+from pyslgr.LLSignal import LLSignal
+from pyslgr.MFCCFeatures import MFCCFeatures
+from pyslgr.FeatPipe import FeatPipe
+from pyslgr.sad import XtalkSAD
+
+if __name__ == "__main__":
+
+    # Load example signal
+    fn = 'signals/example.sph'
+    x = LLSignal()
+    x.load_sph(fn, 0)
+
+    # Initialize feature pipe
+    mfcc_pipe_fn = "config/sid_mfcc+gmmsad_pipe.json"
+    with open(mfcc_pipe_fn, 'r') as fp:
+        pipe_config = json.load(fp)
+    fpipe = FeatPipe(pipe_config, MFCCFeatures, GMMSAD)
+
+    # Get MFCCFeatures
+    f = fpipe.process(x)
+
+    # Info
+    print 'Number of output features: {}'.format(f.num_outfeat())
+    # f.save_raw('tmp/gsv_feat.dat')
+
+    # Load in and create GSV
+    with open('config/gsv.json', 'r') as fp:
+        config = json.load(fp)
+    gsv = GSV(config)
+
+    # Now compute a GSV expansion
+    v = gsv.process(f)
+    print 'A few elements of GSV expansion: {}'.format(v[0:10])
+    print 'GSV expansion dimension = {}'.format(len(v))
+
     print 'Done!  Successfully completed GSV tests'
diff --git a/examples/example_ivec.py b/examples/example_ivec.py
@@ -1,42 +1,42 @@
-#!/usr/bin/env python
-
-import json
-
-from pyslgr.GMMModel import GMMSAD
-from pyslgr.iVector import iVector
-from pyslgr.LLSignal import LLSignal
-from pyslgr.MFCCFeatures import MFCCFeatures
-from pyslgr.FeatPipe import FeatPipe
-import sys
-
-if __name__ == "__main__":
-
-    # Load example signal
-    fn = 'signals/example.sph'
-    x = LLSignal()
-    x.load_sph(fn, 0)
-
-    # Initialize feature pipe
-    mfcc_pipe_fn = "config/sid_mfcc+gmmsad_pipe.json"
-    with open(mfcc_pipe_fn, 'r') as fp:
-        pipe_config = json.load(fp)
-    fpipe = FeatPipe(pipe_config, MFCCFeatures, GMMSAD)
-
-    # Get MFCCFeatures
-    f = fpipe.process(x)
-
-    # Info
-    print 'Number of output features: {}'.format(f.num_outfeat())
-    # f.save_raw('tmp/ivec_feat.dat')
-
-    # Load in and create ivector
-    with open('config/ivec.json', 'r') as fp:
-        config = json.load(fp)
-    ivec = iVector(config)
-
-    # Now compute an ivector
-    v = ivec.process(f)
-    print 'A few elements of iVector: {}'.format(v[0:10])
-    print 'iVector dimension = {}'.format(len(v))
-
+#!/usr/bin/env python
+
+import json
+
+from pyslgr.GMMModel import GMMSAD
+from pyslgr.iVector import iVector
+from pyslgr.LLSignal import LLSignal
+from pyslgr.MFCCFeatures import MFCCFeatures
+from pyslgr.FeatPipe import FeatPipe
+import sys
+
+if __name__ == "__main__":
+
+    # Load example signal
+    fn = 'signals/example.sph'
+    x = LLSignal()
+    x.load_sph(fn, 0)
+
+    # Initialize feature pipe
+    mfcc_pipe_fn = "config/sid_mfcc+gmmsad_pipe.json"
+    with open(mfcc_pipe_fn, 'r') as fp:
+        pipe_config = json.load(fp)
+    fpipe = FeatPipe(pipe_config, MFCCFeatures, GMMSAD)
+
+    # Get MFCCFeatures
+    f = fpipe.process(x)
+
+    # Info
+    print 'Number of output features: {}'.format(f.num_outfeat())
+    # f.save_raw('tmp/ivec_feat.dat')
+
+    # Load in and create ivector
+    with open('config/ivec.json', 'r') as fp:
+        config = json.load(fp)
+    ivec = iVector(config)
+
+    # Now compute an ivector
+    v = ivec.process(f)
+    print 'A few elements of iVector: {}'.format(v[0:10])
+    print 'iVector dimension = {}'.format(len(v))
+
     print 'Done!  Successfully completed iVector tests'