Merge pull request #140 from CPJKU/add_refs_for_downbeats

Add references for ISMIR 2016 RNN/DBN downbeat paper

README.rst

@@ -314,6 +314,11 @@ References
     *An Efficient State Space Model for Joint Tempo and Meter Tracking*,
     Proceedings of the 16th International Society for Music Information
     Retrieval Conference (ISMIR), 2015.
+.. [14] Sebastian Böck, Florian Krebs and Gerhard Widmer,
+    *Joint Beat and Downbeat Tracking with Recurrent Neural Networks*,
+    Proceedings of the 17th International Society for Music Information
+    Retrieval Conference (ISMIR), 2016.
+
 
 
 Acknowledgements

bin/DBNDownBeatTracker

@@ -25,7 +25,10 @@ def main():
     The DBNDownBeatTracker program detects all beats and downbeats in an audio
     file according to the method described in:
 
-    TODO: add reference
+    "Joint Beat and Downbeat Tracking with Recurrent Neural Networks"
+    Sebastian Böck, Florian Krebs and Gerhard Widmer.
+    Proceedings of the 17th International Society for Music Information
+    Retrieval Conference (ISMIR), 2016.
 
     This program can be run in 'single' file mode to process a single audio
     file and write the detected beats to STDOUT or the given output file.

madmom/features/beats.py

@@ -996,7 +996,7 @@ class DBNDownBeatTrackingProcessor(Processor):
 
     MIN_BPM = 55.
     MAX_BPM = 215.
-    NUM_TEMPI = None
+    NUM_TEMPI = 60
     TRANSITION_LAMBDA = 100
     OBSERVATION_LAMBDA = 16
     THRESHOLD = 0.05

madmom/features/beats_hmm.py

@@ -523,6 +523,13 @@ class RNNDownBeatTrackingObservationModel(ObservationModel):
         first representing (down-)beat states and the remaining non-beat
         states.
 
+    References
+    ----------
+    .. [1] Sebastian Böck, Florian Krebs and Gerhard Widmer,
+           "Joint Beat and Downbeat Tracking with Recurrent Neural Networks"
+           Proceedings of the 17th International Society for Music Information
+           Retrieval Conference (ISMIR), 2016.
+
     """
 
     def __init__(self, state_space, observation_lambda):

tests/data/detections/sample.dbn_downbeat_tracker.txt

@@ -1,5 +1,5 @@
 0.090	1
-0.440	2
+0.450	2
 0.790	3
 1.120	4
 1.470	1

tests/test_features_beats.py

@@ -135,9 +135,9 @@ def test_values(self):
         # we have to test each bar length individually
         path, prob = self.processor.hmms[0].viterbi(sample_downbeat_act)
         self.assertTrue(np.allclose(path[:13],
-                                    [11478, 11479, 11480, 11481, 11482, 11483,
-                                     11484, 11485, 217, 218, 219, 220, 221]))
-        self.assertTrue(np.allclose(prob, -766.314167769))
+                                    [7682, 7683, 7684, 7685, 7686, 7687, 7688,
+                                     7689, 217, 218, 219, 220, 221]))
+        self.assertTrue(np.allclose(prob, -764.586595603))
         tm = self.processor.hmms[0].transition_model
         positions = tm.state_space.state_positions[path]
         self.assertTrue(np.allclose(positions[:10],
@@ -149,7 +149,7 @@ def test_values(self):
 
     def test_process(self):
         downbeats = self.processor(sample_downbeat_act)
-        self.assertTrue(np.allclose(downbeats, [[0.09, 1], [0.44, 2],
+        self.assertTrue(np.allclose(downbeats, [[0.09, 1], [0.45, 2],
                                                 [0.79, 3], [1.12, 4],
                                                 [1.47, 1], [1.8, 2],
                                                 [2.14, 3], [2.49, 4]]))