tempo estimation

index.html

@@ -243,6 +243,7 @@ div#notebook {
 <li><a href="signal_representations.html">Signal Representations</a> (<a href="signal_representations.ipynb">ipynb</a>)</li>
 <li><a href="onset_detection.html">Onset Detection</a> (<a href="onset_detection.ipynb">ipynb</a>)</li>
 <li><a href="beat_tracking.html">Beat Tracking</a> (<a href="beat_tracking.ipynb">ipynb</a>)</li>
+<li><a href="tempo_estimation.html">Tempo Estimation</a> (<a href="tempo_estimation.ipynb">ipynb</a>)</li>
 <li><a href="feature_sonification.html">Exercise: Understanding Audio Features through Sonification</a> (<a href="feature_sonification.ipynb">ipynb</a>)</li>
 </ol>
 
@@ -254,7 +255,7 @@ div#notebook {
 </div>
 <div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
-<h2 id="Chapter-2:-Spectral-Feature-Extraction-and-Classification">Chapter 2: Spectral Feature Extraction and Classification<a class="anchor-link" href="#Chapter-2:-Spectral-Feature-Extraction-and-Classification">&#182;</a></h2>
+<h2 id="Chapter-2:-Feature-Extraction">Chapter 2: Feature Extraction<a class="anchor-link" href="#Chapter-2:-Feature-Extraction">&#182;</a></h2>
 </div>
 </div>
 </div>
@@ -264,9 +265,9 @@ div#notebook {
 <div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
 <ol>
+<li><a href="basic_feature_extraction.html">Basic Feature Extraction</a> (<a href="basic_feature_extraction.ipynb">ipynb</a>)</li>
 <li><a href="spectral_features.html">Spectral Features</a> (<a href="spectral_features.ipynb">ipynb</a>)</li>
 <li><a href="mfcc.html">Mel-Frequency Cepstral Coefficients</a> (<a href="mfcc.ipynb">ipynb</a>)</li>
-<li><a href="knn_instrument_classification.html">K-Nearest Neighbor Instrument Classification</a> (<a href="knn_instrument_classification.ipynb">ipynb</a>)</li>
 </ol>
 
 </div>
@@ -287,6 +288,9 @@ div#notebook {
 <div class="inner_cell">
 <div class="text_cell_render border-box-sizing rendered_html">
 <ol>
+<li><a href="basic_supervised_classification.html">Basic Supervised Classification</a> (<a href="basic_supervised_classification.ipynb">ipynb</a>)</li>
+<li><a href="knn.html">K-Nearest Neighbor Classification</a> (<a href="knn.ipynb">ipynb</a>)</li>
+<li><a href="knn_instrument_classification.html">Exercise: K-Nearest Neighbor Instrument Classification</a> (<a href="knn_instrument_classification.ipynb">ipynb</a>)</li>
 <li><a href="notebooks/kmeans.ipynb">K-Means Clustering</a></li>
 <li><a href="exercises/kmeans_instrument_classification.ipynb">Exercise: Unsupervised Instrument Classification using K-Means</a></li>
 </ol>
@@ -358,6 +362,7 @@ div#notebook {
 <li><a href="segmentation.html">Segmentation</a> (<a href="segmentation.ipynb">ipynb</a>)</li>
 <li><a href="beat_tracking_essentia.html">Beat Tracking in Essentia</a> (<a href="beat_tracking_essentia.ipynb">ipynb</a>)</li>
 <li><a href="spectral_features_essentia.html">Spectral Features in Essentia</a> (<a href="spectral_features_essentia.ipynb">ipynb</a>)</li>
+<li><a href="feature_extraction_essentia.html">Feature Extraction in Essentia</a> (<a href="feature_extraction_essentia.ipynb">ipynb</a>)</li>
 </ol>
 
 </div>
@@ -379,8 +384,6 @@ div#notebook {
 <div class="text_cell_render border-box-sizing rendered_html">
 <ol>
 <li><a href="notebooks/tonal.ipynb">Tonal Descriptors: Pitch and Chroma</a></li>
-<li><a href="notebooks/feature_extraction.ipynb">Feature Extraction</a></li>
-<li><a href="notebooks/tempo_estimation.ipynb">Tempo Estimation</a></li>
 </ol>
 
 </div>

index.ipynb

@@ -46,6 +46,7 @@
     "1.  [Signal Representations](signal_representations.html) ([ipynb](signal_representations.ipynb))\n",
     "1.  [Onset Detection](onset_detection.html) ([ipynb](onset_detection.ipynb))\n",
     "1.  [Beat Tracking](beat_tracking.html) ([ipynb](beat_tracking.ipynb))\n",
+    "1.  [Tempo Estimation](tempo_estimation.html) ([ipynb](tempo_estimation.ipynb))\n",
     "1.  [Exercise: Understanding Audio Features through Sonification](feature_sonification.html) ([ipynb](feature_sonification.ipynb))"
    ]
   },
@@ -53,16 +54,16 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Chapter 2: Spectral Feature Extraction and Classification"
+    "## Chapter 2: Feature Extraction"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "1.  [Basic Feature Extraction](basic_feature_extraction.html) ([ipynb](basic_feature_extraction.ipynb))\n",
     "1.  [Spectral Features](spectral_features.html) ([ipynb](spectral_features.ipynb))\n",
-    "1.  [Mel-Frequency Cepstral Coefficients](mfcc.html) ([ipynb](mfcc.ipynb))\n",
-    "1.  [K-Nearest Neighbor Instrument Classification](knn_instrument_classification.html) ([ipynb](knn_instrument_classification.ipynb))"
+    "1.  [Mel-Frequency Cepstral Coefficients](mfcc.html) ([ipynb](mfcc.ipynb))"
    ]
   },
   {
@@ -76,6 +77,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "1.  [Basic Supervised Classification](basic_supervised_classification.html) ([ipynb](basic_supervised_classification.ipynb))\n",
+    "1.  [K-Nearest Neighbor Classification](knn.html) ([ipynb](knn.ipynb))\n",
+    "1.  [Exercise: K-Nearest Neighbor Instrument Classification](knn_instrument_classification.html) ([ipynb](knn_instrument_classification.ipynb))\n",
     "1.  [K-Means Clustering](notebooks/kmeans.ipynb)\n",
     "1.  [Exercise: Unsupervised Instrument Classification using K-Means](exercises/kmeans_instrument_classification.ipynb)"
    ]
@@ -125,7 +129,8 @@
    "source": [
     "1.  [Segmentation](segmentation.html) ([ipynb](segmentation.ipynb))\n",
     "1.  [Beat Tracking in Essentia](beat_tracking_essentia.html) ([ipynb](beat_tracking_essentia.ipynb))\n",
-    "1.  [Spectral Features in Essentia](spectral_features_essentia.html) ([ipynb](spectral_features_essentia.ipynb))"
+    "1.  [Spectral Features in Essentia](spectral_features_essentia.html) ([ipynb](spectral_features_essentia.ipynb))\n",
+    "1.  [Feature Extraction in Essentia](feature_extraction_essentia.html) ([ipynb](feature_extraction_essentia.ipynb))"
    ]
   },
   {
@@ -140,8 +145,8 @@
    "metadata": {},
    "source": [
     "1.  [Tonal Descriptors: Pitch and Chroma](notebooks/tonal.ipynb)\n",
-    "1.  [Feature Extraction](notebooks/feature_extraction.ipynb)\n",
-    "1.  [Tempo Estimation](notebooks/tempo_estimation.ipynb)\n"
+    "\n",
+    "\n"
    ]
   }
  ],

notebooks/tempo_estimation.ipynb

-{
- "metadata": {
-  "name": "",
-  "signature": "sha256:97a0df8e94e03f0ee8b35bdcfeecb7fe032f56066a42d95137d5a30c286d8790"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
-  {
-   "cells": [
-    {
-     "cell_type": "heading",
-     "level": 1,
-     "metadata": {},
-     "source": [
-      "Tempo Estimation"
-     ]
-    },
-    {
-     "cell_type": "heading",
-     "level": 2,
-     "metadata": {},
-     "source": [
-      "`librosa.beat.estimate_tempo`"
-     ]
-    },
-    {
-     "cell_type": "heading",
-     "level": 2,
-     "metadata": {},
-     "source": [
-      "`essentia.standard.Tempo*`"
-     ]
-    },
-    {
-     "cell_type": "code",
-     "collapsed": false,
-     "input": [],
-     "language": "python",
-     "metadata": {},
-     "outputs": []
-    }
-   ],
-   "metadata": {}
-  }
- ]
-}
\ No newline at end of file

stanford_mir/__init__.py

+from core import *

stanford_mir/core.py

+import errno
+import os
+import os.path
+import urllib
+
+def download_drum_samples(path='drum_samples'):
+    """Download ten kick drum samples and ten snare drum samples.
+
+        `path`: output directory containing the twenty drum samples
+
+    Returns:
+
+        `kick_filepaths`: list of kick drum filepaths
+
+        `snare_filepaths`: list of snare drum filepaths
+    """
+    try:
+        os.makedirs(path)
+    except OSError as exception:
+        if exception.errno != errno.EEXIST:
+            raise
+        else:
+            print "Directory %s already exists." % path
+    for drum_type in ['kick', 'snare']:
+        for i in range(1, 11):
+            filename = '%s_%02d.wav' % (drum_type, i)
+            urllib.urlretrieve('http://audio.musicinformationretrieval.com/drum_samples/%s' % filename,
+                               filename=os.path.join(path, filename))
+    kick_filepaths = [os.path.join(path, 'kick_%02d.wav' % i) for i in range(1, 11)]
+    snare_filepaths = [os.path.join(path, 'snare_%02d.wav' % i) for i in range(1, 11)]
+    return kick_filepaths, snare_filepaths