publications

@inproceedings{yogev_system_2008,

title = {A System for Automatic Audio Harmonization ( Ein System f\"{u}r automatische Audio-Harmonisierung)},

author = {Noam Yogev and Alexander Lerch},

url = {http://www.musicinformatics.gatech.edu/wp-content_nondefault/uploads/2016/10/Yogev-and-Lerch-2008-A-System-for-Automatic-Audio-Harmonization-Ein-S-1.pdf},

doi = {10.1.1.148.8391},

year  = {2008},

date = {2008-01-01},

booktitle = {Proceedings of the VdT International Convention (25. Tonmeistertagung)},

address = {Leipzig},

abstract = {A rule-based system for automatic melody harmonization is presented. It models the cognitive process a human arranger undergoes when confronted with the same task, namely: segmenting the melody into phrases, tagging melody notes with harmonic functions, establishing a palette of possible chords for each note, and finding the most agreeable voicing through these chords. The system is designed to be embedded in an audio framework, which synthe- sizes a four-voiced audio output using pitch-shifting techniques. Principles of classical counterpoint as well as common voice-leading conven- tions are utilized by the system. We shall outline the various phases of computa- tion, describe the rules applied in each phase, and present perspectives regarding the stylistic flexibility suggested by the system's design.},

keywords = {audio, harmonization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lerch_requirement_2006,

title = {On the Requirement of Automatic Tuning Frequency Estimation},

author = {Alexander Lerch},

url = {http://dx.doi.org/10.14279/depositonce-2037},

year  = {2006},

date = {2006-01-01},

booktitle = {Proceedings of the International Society for Music Information Retrieval Conference (ISMIR)},

publisher = {ISMIR},

address = {Victoria},

abstract = {The deviation of the tuning frequency from the standard tuning frequency 440 Hz is evaluated for a database of classical music. It is discussed if and under what circumstances such a deviation may affect the robustness of pitch-based systems for musical content analysis.},

keywords = {frequency, tuning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lerch_feapi:_2005,

title = {FEAPI: A Low Level Feature Extraction Plugin API},

author = {Alexander Lerch and Gunnar Eisenberg and Koen Tanghe},

url = {http://www.musicinformatics.gatech.edu/wp-content_nondefault/uploads/2016/10/Lerch-et-al.-2005-FEAPI-A-Low-Level-Feature-Extraction-Plugin-API.pdf},

year  = {2005},

date = {2005-09-01},

booktitle = {Proceedings of 8th International Conference on Digital Audio Effects (DAFX)},

address = {Madrid},

abstract = {This paper presents FEAPI, an easy-to-use platform-independent 

plugin application programming interface (API) for the extraction 

of low level features from audio in PCM format in the context of 

music information retrieval software. The need for and advantages 

of using an open and well-defined plugin interface are outlined in 

this paper and an overview of the API itself and its usage is given.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lerch_ansatz_2004,

title = {Ein Ansatz zur automatischen Erkennung der Tonart in Musikdateien},

author = {Alexander Lerch},

url = {http://www.musicinformatics.gatech.edu/wp-content_nondefault/uploads/2016/10/Lerch-2004-Ein-Ansatz-zur-automatischen-Erkennung-der-Tonart-.pdf},

year  = {2004},

date = {2004-01-01},

booktitle = {Proceedings of the VDT International Audio Convention (23. Tonmeistertagung)},

address = {Leipzig},

abstract = {Es wird ein Verfahren zur automatischen Erkennung der Tonart von Musikdateien vorgestellt. Das Verfahren analysiert mittels einer Filterbank den Tonvorrat des Eingangssignals, der in einem Tonvektor zusammenfasst wird. Dabei sind sowohl mehrstimmige als auch ein- stimmige Eingangssignale zul\"{a}ssig. Mit Hilfe eines Nearest-Neighbour-Classifiers wird anschlie\ss end das wahrscheinlichste Ergebnis f\"{u}r den extrahierten Tonvektor bestimmt. Parallel zur Analyse des Tonvorrats wird die Stimmh\"{o}he des Kammertons detektiert, um eine gleichbleibende Erkennungsrate f\"{u}r Signale unterschiedlicher Stimmh\"{o}he zu gew\"{a}hrleisten.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{burred_hierarchical_2003,

title = {A Hierarchical Approach to Automatic Musical Genre Classification},

author = {Juan Jos\'{e} Burred and Alexander Lerch},

url = {http://www.musicinformatics.gatech.edu/wp-content_nondefault/uploads/2016/10/Burred-and-Lerch-2003-A-Hierarchical-Approach-to-Automatic-Musical-Genre.pdf},

doi = {10.1.1.2.6582},

year  = {2003},

date = {2003-01-01},

booktitle = {Proceedings of the 6th International Conference on Digital Audio Effects (DAFX)},

address = {London},

abstract = {A system for the automatic classification of audio signals according to audio category is presented. The signals are recognized as speech, background noise and one of 13 musical genres. A large number of audio features are evaluated for their suitability in such a classification task, including well-known physical and perceptual features, audio descriptors defined in the MPEG-7 standard, as well as new features proposed in this work. These are selected with regard to their ability to distinguish between a given set of audio types and to their robustness to noise and bandwidth changes. In contrast to previous systems, the feature selection and the classification process itself are carried out in a hierarchical way. This is motivated by the numerous advantages of such a tree-like structure, which include easy expansion capabilities, flexibility in the design of genre-dependent features and the ability to reduce the probability of costly errors. The resulting application is evaluated with respect to classification accuracy and computational costs.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}