use of frame_adapter for IRIT methods

diff --git a/timeside/analyzer/__init__.py b/timeside/analyzer/__init__.py
index 6c8a2fc005cc4bab99b2c88cfe58b1c69f038254..75e8a6ffeb5d7269e57847360f9125105d6d146d 100644 (file)
--- a/timeside/analyzer/__init__.py
+++ b/timeside/analyzer/__init__.py
@@ -14,6 +14,7 @@ from vamp_plugin import VampSimpleHost
 from irit_speech_entropy import IRITSpeechEntropy
 from irit_speech_4hz import IRITSpeech4Hz
 from irit_diverg import IRITDiverg
+from irit_noise_startSilences import IRITStartSeg
 from irit_music_SLN import IRITMusicSLN
 from irit_music_SNB import IRITMusicSNB
 #~ from irit_monopoly import IRITMonopoly

diff --git a/timeside/analyzer/irit_music_SLN.py b/timeside/analyzer/irit_music_SLN.py
index 3a7a63824b4d8f94fbc763f8619c67e932f5ecce..216c2bb313518439f84892674b6676a325fd0e1b 100644 (file)
--- a/timeside/analyzer/irit_music_SLN.py
+++ b/timeside/analyzer/irit_music_SLN.py
@@ -28,18 +28,29 @@ from timeside.api import IAnalyzer
 from numpy import logical_and,array, hamming, dot, mean, float, arange, nonzero
 from numpy.fft import rfft
 from scipy.signal import firwin, lfilter
-from pylab import plot,show
+from timeside.analyzer.preprocessors import frames_adapter
 
 class IRITMusicSLN(Analyzer):
     implements(IAnalyzer)
 
-    def __init__(self, blocksize=1024, stepsize=None) :
+    def __init__(self, blocksize=None, stepsize=None) :
         super(IRITMusicSLN, self).__init__();
+        
         self.parents.append(IRITDiverg())
         self.wLen      = 1.0
         self.wStep     = 0.1
         self.threshold = 20
-        
+        self.input_blocksize = 0;
+        self.input_stepsize = 0;      
+
+    @interfacedoc
+    def setup(self, channels=None, samplerate=None, blocksize=None,
+              totalframes=None):
+        super(IRITMusicSLN, self).setup(
+            channels, samplerate, blocksize, totalframes)
+        self.input_blocksize = int(self.wLen * samplerate)
+        self.input_stepsize = int(self.wStep * samplerate)            
+
     @staticmethod
     @interfacedoc
     def id():
@@ -57,7 +68,8 @@ class IRITMusicSLN(Analyzer):
 
     def __str__(self):
         return "Music confidence indexes"
-
+        
+    @frames_adapter
     def process(self, frames, eod=False):
                
                return frames,eod
@@ -79,9 +91,6 @@ class IRITMusicSLN(Analyzer):
             idx = nonzero(logical_and(segList>(t-w) ,segList<(t+w)))[0]
             segLen[i]= len(idx)
         
-        
-        plot(tLine,segLen)
-        show()
                # Confidence Index
         conf = array(segLen - self.threshold) / self.threshold
         conf[conf > 1] = 1

diff --git a/timeside/analyzer/irit_music_SNB.py b/timeside/analyzer/irit_music_SNB.py
index 15dce01522d1fce9548f2f12b69277b3a57806ac..f1ed5560b3a34dacdd25b8e6df0afc4faf417341 100644 (file)
--- a/timeside/analyzer/irit_music_SNB.py
+++ b/timeside/analyzer/irit_music_SNB.py
@@ -28,17 +28,27 @@ from timeside.api import IAnalyzer
 from numpy import logical_and,array, hamming, dot, mean, float, arange, nonzero
 from numpy.fft import rfft
 from scipy.signal import firwin, lfilter
-from pylab import plot,show
+from timeside.analyzer.preprocessors import frames_adapter
 
 class IRITMusicSNB(Analyzer):
     implements(IAnalyzer)
 
-    def __init__(self, blocksize=1024, stepsize=None) :
+    def __init__(self, blocksize=1024, stepsize=None, samplerate=None) :
         super(IRITMusicSNB, self).__init__();
         self.parents.append(IRITDiverg())
         self.wLen      = 1.0
         self.wStep     = 0.1
+        self.input_blocksize = 0;
+        self.input_stepsize = 0;      
         self.threshold = 20
+
+    @interfacedoc
+    def setup(self, channels=None, samplerate=None, blocksize=None,
+              totalframes=None):
+        super(IRITMusicSNB, self).setup(
+            channels, samplerate, blocksize, totalframes)
+        self.input_blocksize = int(self.wLen * samplerate)
+        self.input_stepsize = int(self.wStep * samplerate)     
         
     @staticmethod
     @interfacedoc
@@ -57,7 +67,8 @@ class IRITMusicSNB(Analyzer):
 
     def __str__(self):
         return "Music confidence indexes"
-
+        
+    @frames_adapter
     def process(self, frames, eod=False):
                
                return frames,eod
@@ -80,10 +91,7 @@ class IRITMusicSNB(Analyzer):
             l = [tLine[t1]-tLine[t2] for t1,t2 in zip()]
             segLen[i]= len(idx)
         
-        
-        plot(tLine,segLen)
-        show()
-               # Confidence Index
+       # Confidence Index
         conf = array(segLen - self.threshold) / self.threshold
         conf[conf > 1] = 1
 

diff --git a/timeside/analyzer/irit_speech_4hz.py b/timeside/analyzer/irit_speech_4hz.py
index ea8667796e33cbb7be7343f7ccb0b7464d14fe33..5771891f9c70633cec0f4cb6db5f987af55c4911 100644 (file)
--- a/timeside/analyzer/irit_speech_4hz.py
+++ b/timeside/analyzer/irit_speech_4hz.py
@@ -27,6 +27,7 @@ from timeside.api import IAnalyzer
 from numpy import array, hamming, dot, mean, float
 from numpy.fft import rfft
 from scipy.signal import firwin, lfilter
+from timeside.analyzer.preprocessors import frames_adapter
 
 
 class IRITSpeech4Hz(Analyzer):
@@ -47,14 +48,20 @@ class IRITSpeech4Hz(Analyzer):
         - modulLen                     (float)         : Length (in second) of the modulation computation window
     '''
 
-    @interfacedoc
+    @interfacedoc    
     def setup(self, channels=None, samplerate=None, blocksize=None,
               totalframes=None):
         super(IRITSpeech4Hz, self).setup(
             channels, samplerate, blocksize, totalframes)
+            
         self.energy4hz = []
         # Classification
         self.threshold = 2.0
+        
+        self.wLen      = 1.0
+        self.wStep     = 0.1
+        self.input_blocksize = int(self.wLen * samplerate)
+        self.input_stepsize = int(self.wStep * samplerate)        
 
         # Pass-band Filter
         self.frequency_center = 4.0
@@ -85,6 +92,7 @@ class IRITSpeech4Hz(Analyzer):
     def __str__(self):
         return "Speech confidences indexes"
 
+    @frames_adapter
     def process(self, frames, eod=False):
         '''
 
@@ -123,7 +131,7 @@ class IRITSpeech4Hz(Analyzer):
 
         # Energy Modulation
         frameLenModulation = int(
-            self.modulLen * self.samplerate() / self.blocksize())
+            self.modulLen * self.samplerate() / self.input_blocksize)
         modEnergyValue = computeModulation(energy, frameLenModulation, True)
 
         # Confidence Index
@@ -154,10 +162,10 @@ class IRITSpeech4Hz(Analyzer):
         segs.label_metadata.label = label
 
         segs.data_object.label = [convert[s[2]] for s in segList]
-        segs.data_object.time = [(float(s[0]) * self.blocksize() /
+        segs.data_object.time = [(float(s[0]) * self.input_blocksize /
                                  self.samplerate())
                                  for s in segList]
-        segs.data_object.duration = [(float(s[1]-s[0]) * self.blocksize() /
+        segs.data_object.duration = [(float(s[1]-s[0]) * self.input_blocksize /
                                      self.samplerate())
                                      for s in segList]
 

diff --git a/timeside/analyzer/irit_speech_entropy.py b/timeside/analyzer/irit_speech_entropy.py
index 8d13ab4bf0ddb271686b985ebf65549be9ce9a53..cdfaec5843ea96ac2d154a06cd3cfe0f72ffb46b 100644 (file)
--- a/timeside/analyzer/irit_speech_entropy.py
+++ b/timeside/analyzer/irit_speech_entropy.py
@@ -26,6 +26,7 @@ from timeside.analyzer.utils import segmentFromValues
 from timeside.api import IAnalyzer
 from numpy import array
 from scipy.ndimage.morphology import binary_opening
+from timeside.analyzer.preprocessors import frames_adapter
 
 
 class IRITSpeechEntropy(Analyzer):
@@ -40,6 +41,10 @@ class IRITSpeechEntropy(Analyzer):
         self.threshold = 0.4
         self.smoothLen = 5
         self.modulLen = 2
+        self.wLen      = 1.0
+        self.wStep     = 0.1
+        self.input_blocksize = int(self.wLen * samplerate)
+        self.input_stepsize = int(self.wStep * samplerate)        
 
     @staticmethod
     @interfacedoc
@@ -58,7 +63,8 @@ class IRITSpeechEntropy(Analyzer):
 
     def __str__(self):
         return "Speech confidences indexes"
-
+        
+    @frames_adapter
     def process(self, frames, eod=False):
         self.entropyValue.append(entropy(frames))
         return frames, eod
@@ -66,7 +72,7 @@ class IRITSpeechEntropy(Analyzer):
     def post_process(self):
 
         entropyValue = array(self.entropyValue)
-        w = self.modulLen * self.samplerate() / self.blocksize()
+        w = self.modulLen * self.samplerate() / self.input_blocksize
         modulentropy = computeModulation(entropyValue, w, False)
         confEntropy = array(modulentropy - self.threshold) / self.threshold
         confEntropy[confEntropy > 1] = 1
@@ -95,10 +101,10 @@ class IRITSpeechEntropy(Analyzer):
         segs.label_metadata.label = label
 
         segs.data_object.label = [convert[s[2]] for s in segList]
-        segs.data_object.time = [(float(s[0]) * self.blocksize() /
+        segs.data_object.time = [(float(s[0]) * self.input_blocksize /
                                  self.samplerate())
                                  for s in segList]
-        segs.data_object.duration = [(float(s[1]-s[0]) * self.blocksize() /
+        segs.data_object.duration = [(float(s[1]-s[0]) * self.input_blocksize /
                                      self.samplerate())
                                      for s in segList]