Samer Abdallah | University College London (original) (raw)

Uploads

Papers by Samer Abdallah

Research paper thumbnail of Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory

Cognitive Science, 2018

A basic function of cognition is to detect regularities in sensory input to facilitate the predic... more A basic function of cognition is to detect regularities in sensory input to facilitate the prediction and recognition of future events. It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different types of statistical information affect listeners’ memory for auditory stimuli. We used a combination of behavioral and computational methods to investigate memory for non-linguistic auditory sequences. Participants repeatedly heard tone sequences varying systematically in their information-theoretic properties. Expectedness ratings of tones were collected during three listening sessions, and a recognition memory test was given after each session. Information-theoretic measures of sequential predictability significantly influenced listeners’ expectedness ratings, and variations in these properties had a significant impact on memory performance. Predictable sequences yielded increasingly better memory performance with increasing exposure. Computational simulations using a probabilistic model of auditory expectation suggest that listeners dynamically formed a new, and increasingly accurate, implicit cognitive model of the information-theoretic structure of the sequences throughout the experimental session.

Research paper thumbnail of Analysing Symbolic Music with Probabilistic Grammars

Computational Music Analysis, 2015

Research paper thumbnail of An information theoretic approach to short-term musical memory

Research paper thumbnail of An Information-Theoretic Account of Musical Expectation and Memory

Research paper thumbnail of Unsupervised analysis of polyphonic music using sparse coding in a probabilistic framework

Research paper thumbnail of Method of Analyzing Audio, Music or Video Data

Research paper thumbnail of Real Time Gesture Learning and Recognition : Towards Automatic Categorization

Research paper thumbnail of Sparse Coding of Music Signals

Page 1. Sparse Coding of Music Signals Samer A. Abdallah*and Mark D. Plumbley1, Department of Ele... more Page 1. Sparse Coding of Music Signals Samer A. Abdallah*and Mark D. Plumbley1, Department of Electronic Engineering King's College London March 13, 2001 Abstract We discuss the use of unsupervised learning techniques ...

Research paper thumbnail of An Independent Component Analysis Approach to Automatic Music Transcription

Research paper thumbnail of Geometric ICA using Nonlinear Correlation And MDS

Research paper thumbnail of Information dynamics

Research paper thumbnail of Unsupervised Learning for Music Perception

ABSTRACT Perception and cognition can be considered to be processes aimed at discovering the inde... more ABSTRACT Perception and cognition can be considered to be processes aimed at discovering the independent causes behind sensory input. Thus, the goal of perception might be to acheive a factorial coding. Unsupervised learning with neural networks offers a way to implement this using techniques such as sparse coding. This would result in a representation in terms of an optimal set of features, rather than the heuristically guided selection often used now. The Wigner Distribution is a good choice of input to these algorithms for a number of reasons. The principle of factorial coding, applied consistently, could result in natural representations for musical contructs such as melodic phrases or rhythmic motives; something which has obvious applications in music processing. 1 Introduction The problem of music cognition is currently being attacked from a number of directions. One approach grows out of work being done on auditory scene analysis [6, 23], starting with an audio signal and modelling, a...

Research paper thumbnail of Exploring probabilistic grammars of symbolic music using PRISM

Research paper thumbnail of Comparing models of symbolic music using probabilistic grammars and probabilistic programming

Research paper thumbnail of How Predictable Do We Like Our Music? Eliciting Aesthetic Preferences With The Melody Triangle Mobile App

Research paper thumbnail of Instantaneous predictive information in Gaussian processes

Research paper thumbnail of Model-based audio source separation

... oai:hal.inria.fr:inria-00545140; Contributeur : Emmanuel Vincent <>; Soumis le ... more ... oai:hal.inria.fr:inria-00545140; Contributeur : Emmanuel Vincent <>; Soumis le : Jeudi 9 Décembre 2010, 16:39:33; Dernière modification le : Vendredi 10 Décembre 2010, 16:02:47. Voir la fiche détaillée. Exporter. Bibtex EndNote ...

Research paper thumbnail of Information theory and sensory perception

Design and Information in Biology, 2006

Research paper thumbnail of Information Dynamics and the Perception of Temporal Structure

Connectionist Models of Behaviour and Cognition Ii, 2009

Research paper thumbnail of Probabilistic Modeling Paradigms for Audio Source Separation

Machine Audition, 2010

... MD, & Davies, ME (2011). Probabilistic Modeling Paradigms for Audio Source Separation. In... more ... MD, & Davies, ME (2011). Probabilistic Modeling Paradigms for Audio Source Separation. In Wang, W. (Ed.), Machine Audition: Principles, Algorithms and Systems. (pp. 162-185). doi:10.4018/978-1-61520-919-4.ch007. Chicago. Vincent, Emmanuel, Maria G. Jafari, Samer ...

Research paper thumbnail of Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory

Cognitive Science, 2018

A basic function of cognition is to detect regularities in sensory input to facilitate the predic... more A basic function of cognition is to detect regularities in sensory input to facilitate the prediction and recognition of future events. It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different types of statistical information affect listeners’ memory for auditory stimuli. We used a combination of behavioral and computational methods to investigate memory for non-linguistic auditory sequences. Participants repeatedly heard tone sequences varying systematically in their information-theoretic properties. Expectedness ratings of tones were collected during three listening sessions, and a recognition memory test was given after each session. Information-theoretic measures of sequential predictability significantly influenced listeners’ expectedness ratings, and variations in these properties had a significant impact on memory performance. Predictable sequences yielded increasingly better memory performance with increasing exposure. Computational simulations using a probabilistic model of auditory expectation suggest that listeners dynamically formed a new, and increasingly accurate, implicit cognitive model of the information-theoretic structure of the sequences throughout the experimental session.

Research paper thumbnail of Analysing Symbolic Music with Probabilistic Grammars

Computational Music Analysis, 2015

Research paper thumbnail of An information theoretic approach to short-term musical memory

Research paper thumbnail of An Information-Theoretic Account of Musical Expectation and Memory

Research paper thumbnail of Unsupervised analysis of polyphonic music using sparse coding in a probabilistic framework

Research paper thumbnail of Method of Analyzing Audio, Music or Video Data

Research paper thumbnail of Real Time Gesture Learning and Recognition : Towards Automatic Categorization

Research paper thumbnail of Sparse Coding of Music Signals

Page 1. Sparse Coding of Music Signals Samer A. Abdallah*and Mark D. Plumbley1, Department of Ele... more Page 1. Sparse Coding of Music Signals Samer A. Abdallah*and Mark D. Plumbley1, Department of Electronic Engineering King's College London March 13, 2001 Abstract We discuss the use of unsupervised learning techniques ...

Research paper thumbnail of An Independent Component Analysis Approach to Automatic Music Transcription

Research paper thumbnail of Geometric ICA using Nonlinear Correlation And MDS

Research paper thumbnail of Information dynamics

Research paper thumbnail of Unsupervised Learning for Music Perception

ABSTRACT Perception and cognition can be considered to be processes aimed at discovering the inde... more ABSTRACT Perception and cognition can be considered to be processes aimed at discovering the independent causes behind sensory input. Thus, the goal of perception might be to acheive a factorial coding. Unsupervised learning with neural networks offers a way to implement this using techniques such as sparse coding. This would result in a representation in terms of an optimal set of features, rather than the heuristically guided selection often used now. The Wigner Distribution is a good choice of input to these algorithms for a number of reasons. The principle of factorial coding, applied consistently, could result in natural representations for musical contructs such as melodic phrases or rhythmic motives; something which has obvious applications in music processing. 1 Introduction The problem of music cognition is currently being attacked from a number of directions. One approach grows out of work being done on auditory scene analysis [6, 23], starting with an audio signal and modelling, a...

Research paper thumbnail of Exploring probabilistic grammars of symbolic music using PRISM

Research paper thumbnail of Comparing models of symbolic music using probabilistic grammars and probabilistic programming

Research paper thumbnail of How Predictable Do We Like Our Music? Eliciting Aesthetic Preferences With The Melody Triangle Mobile App

Research paper thumbnail of Instantaneous predictive information in Gaussian processes

Research paper thumbnail of Model-based audio source separation

... oai:hal.inria.fr:inria-00545140; Contributeur : Emmanuel Vincent <>; Soumis le ... more ... oai:hal.inria.fr:inria-00545140; Contributeur : Emmanuel Vincent <>; Soumis le : Jeudi 9 Décembre 2010, 16:39:33; Dernière modification le : Vendredi 10 Décembre 2010, 16:02:47. Voir la fiche détaillée. Exporter. Bibtex EndNote ...

Research paper thumbnail of Information theory and sensory perception

Design and Information in Biology, 2006

Research paper thumbnail of Information Dynamics and the Perception of Temporal Structure

Connectionist Models of Behaviour and Cognition Ii, 2009

Research paper thumbnail of Probabilistic Modeling Paradigms for Audio Source Separation

Machine Audition, 2010

... MD, & Davies, ME (2011). Probabilistic Modeling Paradigms for Audio Source Separation. In... more ... MD, & Davies, ME (2011). Probabilistic Modeling Paradigms for Audio Source Separation. In Wang, W. (Ed.), Machine Audition: Principles, Algorithms and Systems. (pp. 162-185). doi:10.4018/978-1-61520-919-4.ch007. Chicago. Vincent, Emmanuel, Maria G. Jafari, Samer ...

Log In