“Reinventing the Wheel”: A Novel Approach to Music Player Interfaces

We present a novel interface to (portable) music players that benefit from intelligently structured collections of audio files. For structuring, we calculate similarities between every pair of songs and model a travelling salesman problem (TSP) that is solved to obtain a playlist (i.e., the track ordering during playback) where the average distance between consecutive pieces of music is minimal according to the similarity measure. The similarities are determined using both audio signal analysis of the music tracks and Web-based artist profile comparison. Indeed, we show how to enhance the quality of the well-established methods based on audio signal processing with features derived from Web pages of music artists. Using TSP allows for creating circular playlists that can be easily browsed with a wheel as input device. We investigate the usefulness of four different TSP algorithms for this purpose. For evaluating the quality of the generated playlists, we apply a number of quality measures to two real-world music collections. It turns out that the proposed combination of audio and text-based similarity yields better results than the initial approach based on audio data only. We implemented an audio player as Java applet to demonstrate the benefits of our approach. Furthermore, we present the results of a small user study conducted to evaluate the quality of the generated playlists

[1]  Peter Knees,et al.  Assigning and Visualizing Music Genres by Web-based Co-Occurrence Analysis , 2006, ISMIR.

[2]  François Pachet,et al.  Improving Timbre Similarity : How high’s the sky ? , 2004 .

[3]  Ahmed H. Tewfik,et al.  A network flow model for playlist generation , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[4]  Beth Logan,et al.  Content-Based Playlist Generation: Exploratory Experiments , 2002, ISMIR.

[5]  Éva Tardos,et al.  Algorithm design , 2005 .

[6]  Tim Pohle Extraction of Audio Descriptors and Their Evaluation in Music Classification Tasks , 2005 .

[7]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[8]  Beth Logan,et al.  A music similarity function based on signal analysis , 2001, IEEE International Conference on Multimedia and Expo, 2001. ICME 2001..

[9]  François Pachet,et al.  Scaling up music playlist generation , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[10]  Tim Pohle,et al.  GENERATING SIMILARITY-BASED PLAYLISTS USING TRAVELING SALESMAN ALGORITHMS , 2005 .

[11]  Markus Schedl,et al.  Intelligent structuring and exploration of digital music collections , 2005 .

[12]  Beth Logan,et al.  Mel Frequency Cepstral Coefficients for Music Modeling , 2000, ISMIR.

[13]  A. H. Tewfik,et al.  A network flow model for playlist generation , 2001 .

[14]  François Pachet,et al.  "The way it Sounds": timbre models for analysis and retrieval of music signals , 2005, IEEE Transactions on Multimedia.

[15]  David S. Johnson,et al.  The Traveling Salesman Problem: A Case Study in Local Optimization , 2008 .

[16]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[17]  François Pachet,et al.  Music Similarity Measures: What's the use? , 2002, ISMIR.

[18]  Elias Pampalk,et al.  Using Smoothed Data Histograms for Cluster Visualization in Self-Organizing Maps , 2002, ICANN.

[19]  George Tzanetakis,et al.  Interactive Content-Aware Music Browsing using the Radio Drum , 2006, 2006 IEEE International Conference on Multimedia and Expo.

[20]  Masataka Goto,et al.  Musicream: New Music Playback Interface for Streaming, Sticking, Sorting, and Recalling Musical Pieces , 2005, ISMIR.

[21]  Gerard Salton,et al.  Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..

[22]  George Tzanetakis MUSESCAPE: AN INTERACTIVE CONTENT-AWARE MUSIC BROWSER , 2003 .

[23]  Keld Helsgaun,et al.  An effective implementation of the Lin-Kernighan traveling salesman heuristic , 2000, Eur. J. Oper. Res..

[24]  Teofilo F. Gonzalez,et al.  P-Complete Approximation Problems , 1976, J. ACM.

[25]  Elias Pampalk,et al.  Content-based organization and visualization of music archives , 2002, MULTIMEDIA '02.