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Documents authored by Liem, Cynthia C.S.

Document
DOI: 10.4230/DFU.Vol3.11041.135
User-Aware Music Retrieval

Authors: Markus Schedl, Sebastian Stober, Emilia Gómez, Nicola Orio, and Cynthia C.S. Liem

Published in: Dagstuhl Follow-Ups, Volume 3, Multimodal Music Processing (2012)

Abstract
Personalized and user-aware systems for retrieving multimedia items are becoming increasingly important as the amount of available multimedia data has been spiraling. A personalized system is one that incorporates information about the user into its data processing part (e.g., a particular user taste for a movie genre). A context-aware system, in contrast, takes into account dynamic aspects of the user context when processing the data (e.g., location and time where/when a user issues a query). Today's user-adaptive systems often incorporate both aspects. Particularly focusing on the music domain, this article gives an overview of different aspects we deem important to build personalized music retrieval systems. In this vein, we first give an overview of factors that influence the human perception of music. We then propose and discuss various requirements for a personalized, user-aware music retrieval system. Eventually, the state-of-the-art in building such systems is reviewed, taking in particular aspects of "similarity" and "serendipity" into account.
Cite as

Markus Schedl, Sebastian Stober, Emilia Gómez, Nicola Orio, and Cynthia C.S. Liem. User-Aware Music Retrieval. In Multimodal Music Processing. Dagstuhl Follow-Ups, Volume 3, pp. 135-156, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InCollection{schedl_et_al:DFU.Vol3.11041.135,
  author =	{Schedl, Markus and Stober, Sebastian and G\'{o}mez, Emilia and Orio, Nicola and Liem, Cynthia C.S.},
  title =	{{User-Aware Music Retrieval}},
  booktitle =	{Multimodal Music Processing},
  pages =	{135--156},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-37-8},
  ISSN =	{1868-8977},
  year =	{2012},
  volume =	{3},
  editor =	{M\"{u}ller, Meinard and Goto, Masataka and Schedl, Markus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol3.11041.135},
  URN =		{urn:nbn:de:0030-drops-34709},
  doi =		{10.4230/DFU.Vol3.11041.135},
  annote =	{Keywords: user-aware music retrieval, personalization, recommendation, user context, adaptive systems, similarity measurement, serendipity}
}
Document
DOI: 10.4230/DFU.Vol3.11041.195
Music Information Retrieval: An Inspirational Guide to Transfer from Related Disciplines

Authors: Felix Weninger, Björn Schuller, Cynthia C.S. Liem, Frank Kurth, and Alan Hanjalic

Published in: Dagstuhl Follow-Ups, Volume 3, Multimodal Music Processing (2012)

Abstract
The emerging field of Music Information Retrieval (MIR) has been influenced by neighboring domains in signal processing and machine learning, including automatic speech recognition, image processing and text information retrieval. In this contribution, we start with concrete examples for methodology transfer between speech and music processing, oriented on the building blocks of pattern recognition: preprocessing, feature extraction, and classification/decoding. We then assume a higher level viewpoint when describing sources of mutual inspiration derived from text and image information retrieval. We conclude that dealing with the peculiarities of music in MIR research has contributed to advancing the state-of-the-art in other fields, and that many future challenges in MIR are strikingly similar to those that other research areas have been facing.
Cite as

Felix Weninger, Björn Schuller, Cynthia C.S. Liem, Frank Kurth, and Alan Hanjalic. Music Information Retrieval: An Inspirational Guide to Transfer from Related Disciplines. In Multimodal Music Processing. Dagstuhl Follow-Ups, Volume 3, pp. 195-216, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

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@InCollection{weninger_et_al:DFU.Vol3.11041.195,
  author =	{Weninger, Felix and Schuller, Bj\"{o}rn and Liem, Cynthia C.S. and Kurth, Frank and Hanjalic, Alan},
  title =	{{Music Information Retrieval: An Inspirational Guide to Transfer from Related Disciplines}},
  booktitle =	{Multimodal Music Processing},
  pages =	{195--216},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-37-8},
  ISSN =	{1868-8977},
  year =	{2012},
  volume =	{3},
  editor =	{M\"{u}ller, Meinard and Goto, Masataka and Schedl, Markus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol3.11041.195},
  URN =		{urn:nbn:de:0030-drops-34737},
  doi =		{10.4230/DFU.Vol3.11041.195},
  annote =	{Keywords: Feature extraction, machine learning, multimodal fusion, evaluation, human factors, cross-domain methodology transfer}
}
Document
DOI: 10.4230/DFU.Vol3.11041.227
Music Information Technology and Professional Stakeholder Audiences: Mind the Adoption Gap

Authors: Cynthia C.S. Liem, Andreas Rauber, Thomas Lidy, Richard Lewis, Christopher Raphael, Joshua D. Reiss, Tim Crawford, and Alan Hanjalic

Published in: Dagstuhl Follow-Ups, Volume 3, Multimodal Music Processing (2012)

Abstract
The academic discipline focusing on the processing and organization of digital music information, commonly known as Music Information Retrieval (MIR), has multidisciplinary roots and interests. Thus, MIR technologies have the potential to have impact across disciplinary boundaries and to enhance the handling of music information in many different user communities. However, in practice, many MIR research agenda items appear to have a hard time leaving the lab in order to be widely adopted by their intended audiences. On one hand, this is because the MIR field still is relatively young, and technologies therefore need to mature. On the other hand, there may be deeper, more fundamental challenges with regard to the user audience. In this contribution, we discuss MIR technology adoption issues that were experienced with professional music stakeholders in audio mixing, performance, musicology and sales industry. Many of these stakeholders have mindsets and priorities that differ considerably from those of most MIR academics, influencing their reception of new MIR technology. We mention the major observed differences and their backgrounds, and argue that these are essential to be taken into account to allow for truly successful cross-disciplinary collaboration and technology adoption in MIR.
Cite as

Cynthia C.S. Liem, Andreas Rauber, Thomas Lidy, Richard Lewis, Christopher Raphael, Joshua D. Reiss, Tim Crawford, and Alan Hanjalic. Music Information Technology and Professional Stakeholder Audiences: Mind the Adoption Gap. In Multimodal Music Processing. Dagstuhl Follow-Ups, Volume 3, pp. 227-246, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2012)

Copy BibTex To Clipboard

@InCollection{liem_et_al:DFU.Vol3.11041.227,
  author =	{Liem, Cynthia C.S. and Rauber, Andreas and Lidy, Thomas and Lewis, Richard and Raphael, Christopher and Reiss, Joshua D. and Crawford, Tim and Hanjalic, Alan},
  title =	{{Music Information Technology and Professional Stakeholder Audiences: Mind the Adoption Gap}},
  booktitle =	{Multimodal Music Processing},
  pages =	{227--246},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-37-8},
  ISSN =	{1868-8977},
  year =	{2012},
  volume =	{3},
  editor =	{M\"{u}ller, Meinard and Goto, Masataka and Schedl, Markus},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol3.11041.227},
  URN =		{urn:nbn:de:0030-drops-34759},
  doi =		{10.4230/DFU.Vol3.11041.227},
  annote =	{Keywords: music information retrieval, music computing, domain expertise, technology adoption, user needs, cross-disciplinary collaboration}
}
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