Tag Archives: artificial intelligence

Human and Machine Intelligence: a Music Information Retrieval perspective

I had the honor to be invited as keynote speaker at the International Conference on Computational Creativity 2020. The conference took place in a virtual format given the health emergency situation. In my talk, I discussed on the different motivations for music information retrieval, the paradigm shift from knowledge-driven to data-driven systems, the main challenges of this field of research and its impact on society.

It was an interesting experience to give a virtual keynote. First, it was a lot of work to prepare for the keynote, including recording the video properly at home. In addition, I missed the experience of seeing people’s faces and expression when listening to your talk. This visual feedback is really important to see how people react to the different parts of your talk. And I missed the travel and visit to beautiful Coimbra. Virtual events also have positive sides, as the confort of speaking at home, accessibility for anyone in the world to follow on streaming, and all energy saved by people not travelling to sites.

You can watch it in youtube! Any comment or feedback is welcome.

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Research on child-robot interaction

In the context of the HUMAINT (Human behaviour and machine intelligence) project, we research on the impact that social robots have on children. In this context, I have had the chance to carry out my first research on the amazing field of child-robot interaction, thanks to the collaboration with Vicky Charisi, Luis Merino and their lab at Universidad Pablo Olavide and Honda Research Institute Japan.

Running a user study with children and robots is very challenging from a technical perspective, and  analysing their data is challenging as well.  We just published in frontiers the result of our first study, where we experimented with two strategies for child-robot interaction in a problem solving task: turn taking and child-initiated interaction, and we showed the need for this voluntary interaction. You can check the details below. It is amazing to learn and contribute to research on this topic!

Child-Robot Collaborative Problem-Solving and the Importance of Child’s Voluntary Interaction: A Developmental Perspective

Vicky Charisi, Emilia Gomez, Gonzalo Mier, Luis Merino and Randy Gomez

Abstract: The emergence and development of cognitive strategies for the transition from exploratory actions towards intentional problem-solving in children is a key question for the understanding of the development of human cognition. Researchers in developmental psychology have studied cognitive strategies and have highlighted the catalytic role of the social environment. However, it is not yet adequately understood how this capacity emerges and develops in biological systems when they perform a problem-solving task in collaboration with a robotic social agent. This paper presents an empirical study in a human-robot interaction (HRI) setting which investigates children’s problem-solving from a developmental perspective. In order to theoretically conceptualize children’s developmental process of problem-solving in HRI context, we use principles based on the intuitive theory and we take into consideration existing research on executive functions with a focus on inhibitory control. We considered the paradigm of the Tower of Hanoi and we conducted an HRI behavioral experiment to evaluate task performance. We designed two types of robot interventions, “voluntary” and “turn-taking”—manipulating exclusively the timing of the intervention. Our results indicate that the children who participated in the voluntary interaction setting showed a better performance in the problem solving activity during the evaluation session despite their large variability in the frequency of self-initiated interactions with the robot. Additionally, we present a detailed description of the problem-solving trajectory for a representative single case-study, which reveals specific developmental patterns in the context of the specific task. Implications and future work are discussed regarding the development of intelligent robotic systems that allow child-initiated interaction as well as targeted and not constant robot interventions.


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Journal paper on AI and Music: Open Questions of Copyright Law and Engineering Praxis

I am very happy to share with you the publication of a truly interdisciplinary study on the impact of AI on music, including considerations from copyright and engineering praxis. It has been an amazing experience to collaborate with scholars in the field of creative practices, engineering and law, and I hope the paper will serve to start discussing some relevant aspects related to the use of AI in music production.


The application of artificial intelligence (AI) to music stretches back many decades, and presents numerous unique opportunities for a variety of uses, such as the recommendation of recorded music from massive commercial archives, or the (semi-)automated creation of music. Due to unparalleled access to music data and effective learning algorithms running on high-powered computational hardware, AI is now producing surprising outcomes in a domain fully entrenched in human creativity—not to mention a revenue source around the globe. These developments call for a close inspection of what is occurring, and consideration of how it is changing and can change our relationship with music for better and for worse. This article looks at AI applied to music from two perspectives: copyright law and engineering praxis. It grounds its discussion in the development and use of a specific application of AI in music creation, which raises further and unanticipated questions. Most of the questions collected in this article are open as their answers are not yet clear at this time, but they are nonetheless important to consider as AI technologies develop and are applied more widely to music, not to mention other domains centred on human creativity.

Keywords: artificial intelligence; music; copyright; engineering; ethics


Paper available in open access at Arts journal.

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Women in AI: mitigating the gender bias

Last Friday March 8th I was invited to speak at a lunch event of the European Commission intended to provide a scientific perspective to the challenges of gender equality. I gave a talk titled “Women in Artificial Intelligence: mitigating the gender bias”, that is summarized here.

In this context today my colleague Ana Freire and I are launching the divinAI initative to monitor the presence of women in AI events. Please come to our HACKFEST event in Barcelona in June 1st! 



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El dilema de la tecnología ética – The dilemma of ethical technologies

Article in Spanish about ethics of technology written by Esther Paniagua in the context of the HUMAINT winter school that took place this month at JRC Seville. The article is also available online.

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Entrevista en el mundo sobre inteligencia artificial

Entrevista en el mundo por Silvia Moreno sobre la inteligencia artificial y el impacto que está y tendrá en el futuro en las personas

https://www.elmundo.es/papel/lideres/201 8/09/25/5ba81ccb268e3eee488b462d.html   


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A los seres humanos siempre nos quedará la creatividad, una máquina no puede crear ¿mito o realidad?

Un artículo muy interesante de Esther Paniagua sobre la creatividad computacional donde comento que un algoritmo de generación de sonido o música puede ser creativo por sí mismo y generar material musical interesante, complementando la creatividad humana. El artículo incluye muchos ejemplos interesantes de arte creado por algoritmos y de opiniones sobre si las máquinas pueden crear. Pues sí, es una realidad!


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Saltando como locos de una canción a otra

Así se titula el reportaje de Joseba Elola que se publicó el 29 de Noviembre en el monográfico de música del País semanal, en donde refleja nuestra conversación telefónica donde intenté explicar de manera clara cómo funcionan los sistemas de recomendación musical:

Estos sistemas de recomendación procesan datos editoriales de las canciones como sus títulos o los nombres de los artistas; datos del sonido, como el timbre de la voz, los patrones rítmicos o la escala; e información de los usuarios que han escuchado esa música: si a alguien a quien le gusta Leonard Cohen también le gusta Rufus Wainwright, el algoritmo lo identifica y manda una canción del segundo a aquel que está escuchando al primero. Así lo explica Emilia Gómez, ingeniera de telecomunicaciones especializada en los sistemas de recuperación de la información musical (en inglés, music information retrieval) y presidenta de International Society of Music Information Retrieval (ISMIR), comunidad académica que investiga las tecnologías de recomendación —y con la que colaboran Spotify, Apple o Amazon Music—.

Analizando los instrumentos que suenan, el timbre, la melodía, el ritmo, la estructura de la canción, las voces y el estilo, se confecciona un modelo de los gustos de cada persona, advierte Gómez en conversación telefónica desde Sevilla. “Estos sistemas son cada vez más complejos”, dice, “y las bases de datos, más grandes”. De modo que la tecnología es cada vez más precisa, mejor. 

Esa es la parte buena de la ecuación. La mala, que el predominio de las listas cocinadas por las plataformas acabe por uniformizar lo que escuchamos. “Cuanta más gente hay en las plataformas, mejor funcionan los algoritmos”, manifiesta Gómez. “Mejor, sobre todo, si te gusta lo que a la mayoría. Los que escuchan propuestas raras o minoritarias verán que esa música no se recomienda porque no hay mucha gente que la escuche. Así, se reproduce el sistema que teníamos en la antigüedad, cuando solo un tipo de música se hacía popular, la que te recomendaba la radio”.

No es sólo importante que éstos algoritmos pueden uniformizar  lo que escuchamos, lo cual está relacionado con el denominado efecto “larga cola” en el que siempre se recomienda un pequeño repertorio. Un efecto aún más desconocido es la especialización excesiva del gusto musical que se deriva de la personalización, y que pueden crear éste tipo de algoritmos basados en similitud. En el proyecto HUMAINT estamos estudiando éste efecto, que se conoce como ¨filtro burbuja“, dentro del análisis del impacto de la inteligencia artificial en las personas.


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Keynote speech @ 2018 Joint Workshop on Machine Learning for Music – ICML


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. T

In my keynote, I presented some current research of our lab on the analysis and synthesis of singing. In particular, we summarized some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques. We discussed their achievements in terms of accuracy and sound quality, and the current challenges, such as availability of data and computing resources. We also discussed the impact that these advances do and will have on listeners and singers when they are integrated in commercial applications.

There is paper related to this research which can be found in arxiv.


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Interview at ACM SIGMM Records and the need for interdisciplinary research

The March Issue (Vol.10, Issue 1) of ACM SIGMM Records (News for the Multimedia Community) is out and it includes an interview of myself for the interdisciplinary column, kindly chaired by Cynthia Liem and Jochen Huber.

It is awesome already that there is an interdisciplinary column at SIGMM, recognising the challenges and also the potential of interdisciplinary research and insights as a way to have a comprehensive understanding, in this case, of multimedia computing. I was very pleased to ask questions about my experience in the MIR field and about diversity and interdisciplinarity.

You can read the interview and other interesting content here.

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