Cognitive Audio Interfaces: Mediating Sonic Information With an Understanding of How We Hear

Ananthabhotla, Ishwarya; Ramsay, David B.; Duhart, Clément; Paradiso, Joseph A.

doi:10.1109/mprv.2021.3052659

Cited by 2 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most studies related to the assessment of emotions, dimensional models are used, they are most common in the studies of B. Schuller and K. Drossos [1][2][3]. This study uses a discrete model of emotions, as the aim is to ISSN 2710-0766…”

Section: Related Workmentioning

confidence: 99%

Creating a Model of the Influence of Sounds on the Emotional State of Man

Havrysh¹,

Tymchenko²

2022

CSIT

View full text Add to dashboard Cite

The environment is full of various sounds - signals registered by human and animal hearing organs, which in terms of frequency and strength merge into a monotonous, incoherent sound. The physical carriers of signals reaching the hearing organs are acoustic (sound) waves – mechanical waves that propagate in the air and are perceived by the hearing organs. Human hearing organs can perceive sounds in a fairly wide range of frequencies and intensities. The range of sounds heard by a person is limited by two threshold curves: the lower one is the threshold of perception, the upper one is the threshold of pain sensations. The human hearing threshold is 0 dB at a frequency of 1000 Hz, and the pain threshold occurs from a sound of 140 dB [2]. As long as there have been wars, it is known that mass battle cries and drumbeats oppress the enemy. The sirens of attack planes and bombers make him feel terrified and want to run away. Now an explanation has been found for this: loud sounds excite a person, contribute to the influx of a large amount of hormones into the blood, in particular, adrenaline, as a result of which there is a feeling of danger and fear [3]. There is a description of existing approaches to assess the impact of sounds on the emotional state of man, which will be the first step towards creating a model for analyzing the impact of sounds on the emotional state of man based on the theory of discrete emotions. Generated values for emotional evaluation of sounds.

show abstract

Section: Related Workmentioning

confidence: 99%

Creating a Model of the Influence of Sounds on the Emotional State of Man

Havrysh¹,

Tymchenko²

2022

CSIT

View full text Add to dashboard Cite

show abstract

“…Of these, the hybrid approach remains the most promising, particularly when combined with the power of recent deep-learning models (cf. Turian et al [5], Elizalde et al [6]., Pranay et al [7], Anderson et al [8], Tashev et al [9], Ananthabhotla [10], Wang et al [11], Zeghidour et al [12]). We define hybrid approaches as approaches that learn from datadriven methods and use knowledge about human perception and cognition to constrain the optimization problem and make end-to-end learning easier.…”

Section: Introductionmentioning

confidence: 99%

Synergy between human and machine approaches to sound/scene recognition and processing: An overview of ICASSP special session

Heller¹,

Elizalde²,

Raj³

et al. 2023

Preprint

View full text Add to dashboard Cite

Machine Listening, as usually formalized, attempts to perform a task that is, from our perspective, fundamentally human-performable, and performed by humans. Current automated models of Machine Listening vary from purely datadriven approaches to approaches imitating human systems. In recent years, the most promising approaches have been hybrid in that they have used data-driven approaches informed by models of the perceptual, cognitive, and semantic processes of the human system. Not only does the guidance provided by models of human perception and domain knowledge enable better, and more generalizable Machine Listening, in the converse, the lessons learned from these models may be used to verify or improve our models of human perception themselves. This paper summarizes advances in the development of such hybrid approaches, ranging from Machine Listening models that are informed by models of peripheral (human) auditory processes, to those that employ or derive semantic information encoded in relations between sounds. The research described herein was presented in a special session on "Synergy between human and machine approaches to sound/scene recognition and processing" (ICASSP 2023).

show abstract

Cognitive Audio Interfaces: Mediating Sonic Information With an Understanding of How We Hear

Cited by 2 publications

References 11 publications

Creating a Model of the Influence of Sounds on the Emotional State of Man

Creating a Model of the Influence of Sounds on the Emotional State of Man

Synergy between human and machine approaches to sound/scene recognition and processing: An overview of ICASSP special session

Contact Info

Product

Resources

About