Tag Archives: music

Keynote speech at the 2018 Joint Workshop on Machine Learning for Music

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I am honored to be keynote speaker at a joint workshop on Machine Learning for Music that will take place this summer in Stockholm. I spent part of my PhD in KTH in Stockholm and it became one of my favourite places, so it is always great to visit. This is the call for papers! I encourage all of you to submit as it will be a fun event!

2nd Call-for-Papers for the 2018 Joint Workshop on Machine Learning for Music, a joint workshop program of IJCAI/ECAI, AAMAS, and ICML

Stockholm, Sweden

July 14-15, 2018 (Tentative dates)

https://sites.google.com/site/faimmusic2018/

Keynote Speaker:

  • Emilia Gómez, Joint Research Centre (European Commission) and Universitat Pompeu Fabra

Invited Speakers:

  • Anna Huang, Google
  • Matt McVicar, Jukedeck
  • Bob Sturm, Queen Mary University of London

The ever-increasing size and accessibility of vast music libraries has created a demand more than ever for machine learning systems that are capable of understanding and organizing this complex data. Further, the whole music ecosystem –from creation to consumption– is being disrupted to its core by current developments in machine learning, and in particular recent advances in deep learning. The topics discussed in the workshop will span a variety of music generation and recommender systems challenges including cross-cultural recommendation, content-based audio processing and representation learning, automatic music tagging, synthesis, style-transfer, and evaluation.

We invite the research community, from both industry and academia, to submit 2-page extended abstracts on topics such as:

  • Music recommendation and discovery
  • AI-based music creation and machine creativity
  • Content-based and multimodal music recommender systems
  • Transfer learning and semi-supervised learning for music discovery
  • Audio and semantic content-based machine learning (e.g., genre, mood, style, rhythm)
  • Browsing and visualization of large music and listener datasets
  • Similarity metric learning
  • Learning to rank
  • Evaluation methodology
  • Deep learning applications for computational music research
  • Modeling hierarchical and long term music structures using deep learning
  • Modeling ambiguity and preference in music
  • Software frameworks and tools for deep learning in music
  • Automatic classification of music (audio and MIDI)
  • Style-based interpreter recognition
  • Automatic composition and improvisation
  • Automatic score alignment
  • Polyphonic pitch detection, Chord extraction, and Pattern discovery
  • Expressive performance modeling

2-page extended abstracts should be formatted according to the ICML template:

https://media.nips.cc/Conferences/ICML2018/Styles/icml2018_style.tar.gz

Word templates will not be provided. Only papers using the above template will be considered.

Papers should be submitted via email to the following address: joint-music-machine-learning-workshop@googlegroups.com

Accepted papers will be published online.

Important Dates:

  • Abstract submission deadline: May 18, 2018
  • Notifications: May 25, 2018
  • Camera-ready deadline: July 6, 2018
  • Workshop: July 14-15, 2018

 Check the website (https://sites.google.com/site/faimmusic2018/ ) for more details, and regular updates on invited speakers.

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Interview with Tara Chklovski from Iridescent Learning

Las December I had the chance to virtually meet Tara Chklovski, who is the CEO of Iridescent Learning,  a science education nonprofit organization in the United States.

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Their mission, according to their website, is “to empower the world´s underrepresented young people, especially girls, through engineering and technology to become innovators and leader”.

They just launched (with AAAI, a leading organization in Artificial Intelligence) — the first, global Curiosity Machine AI Family Challenge – a two-stage competition for 20,000 underserved 3rd-8th grade students and parents (especially mothers) to use AI technologies and tools (sensors, data analysis tools) to solve problems in their communities (along the tracks of health, energy, food, transportation, education, public safety and civic engagement).

Of course, I thought: “what a wonderful mission and challenges!” How can I help? So she proposed me to do an interview where I could provide my thoughts on AI and its impact, targeting this particular audience.

 

It took me some weeks to complete it, as I have been very busy moving to another city, but I managed to answer the questions I hope in an interesting way. I hope this can also help to disseminate our research community, ISMIR, and its efforts to increase inclusion and variety, WiMIR, which I am very proud to contribute to.

I hope you like the interview, which can be found here.

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Hello world: el ¿primer? álbum ¿creado? por ¿inteligencia? artificial. 

Hoy en el programa de Radio Clásica, Longitud de Onda #LDOnda explicaré cuál ha sido el proceso de elaboración de “Hello world“, que según sus creadores es el primer álbum creado por inteligencia artificial.

Podréis escuchar el programa hoy en directo o más tarde en los podcasts de Longitud de Onda. También podéis escuchar otros programas en los que he participado aquí.

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¿Qué impacto tendrá la inteligencia artificial en el comportamiento humano?

Noticia en la web de la UPF sobre el nuevo proyecto HUMAINT

Podéis leerla aquí.

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Resumen de mi colaboración con el programa Longitud de Onda

Aprovechando las vacaciones, he hecho una lista todos los programas de Longitud de Onda, espacio de Radio Clásica, en donde he tenido la suerte de colaborar. Ha sido una gran experiencia donde he aprendido mucho sobre divulgación científica y cómo hablar por la radio, lo cual no es uno de mis fuertes. Creo que se nota bastante el cambio entre el primer y el último programa, así que ¡gracias a Yolanda y Fernando por la confianza!.

¡Aquí los tenéis!

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KNOWeSCAPE: Analyzing the dynamics of information and knowledge landscapes

A late post about an amazing event. As pointed out in their website, there is no scape from the expansion of information! Yes, we need strategies for structuring, visualizing and locating what you need.

I have been getting more and more interested on the role of music visualization. There has been a large amount of research within the Music Information Retrieval (MIR) field intended to extract meaningful descriptions from music in audio format, to compute similarity between music pieces and to classify them according to semantic concepts such as mood, style or preference. However, less effort has been devoted to investigate which are the best strategies to present, in a visual way, this information to users with different profiles (e.g. expert musicians and people with no theoretical musical knowledge) and in different contexts (e.g. music listening or education). The main challenges are to provide intuitive visualizations of large music collections, to present information related to different temporal scales  (from real-time to global descriptors), and to combine descriptions related to different musical facets such as score, rhythm, tonality or instrumentation.

I had the chance to be invited as a speaker to a workshop on knowledge order an science. In this talk I presented some of our approaches to music visualization in terms of tonality, dynamics, tempo, structure, mood and music preference. I also discussed how these approaches are being considered in the PHENICX project to enrich live music concert performances in classical music. I also wanted to discuss about the need of multi-scale, personalized and adaptive representations of music collections.

It was a great event, and you can find on the web the abstracts of the different presentations and the slides. There is also here a summary of the workshop. It was an enriching multi-disciplinary experience, I was happy to see more women than is usually in tech events and now I have the chance to be part of this COST action and great community. Let me illustrate that with a figure from Agustin Martorell’s thesis.

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