2016Unpublished venueRequires access

A review on conventional psychoacoustic evaluation tools, methods and algorithms

Alexander Stojanow, Judith Liebetrau

Open publisher page 2 citations

Abstract

Nowadays, psychoacoustic analysis of a sound is often applied for quick quantification of its auditory perception. Such hearing-related quantities also referred to as psychoacoustic parameters are meant to be a good representation of the human auditory perception. Predictive models are available to estimate the perception of these quantities. However, calculated psychoacoustic parameters show a lack of accuracy when compared with subjective listening test results for complex and authentic sounds. This paper shows some deficiencies and strengths of conventional algorithms and offers a few ideas for improvement.

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What this paper is about

Nowadays, psychoacoustic analysis of a sound is often applied for quick quantification of its auditory perception. Such hearing-related quantities also referred to as psychoacoustic parameters are meant to be a good representation of the human auditory perception. Predictive models are available to estimate the perception of these quantities. However, calculated psychoacoustic parameters show a lack of accuracy when compared with subjective listening test results for complex and authentic sounds. This paper shows some deficiencies and strengths of conventional algorithms and offers a few ideas for improvement.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Nowadays, psychoacoustic analysis of a sound is often applied for quick quantification of its auditory perception. Such hearing-related quantities also referred to as psychoacoustic parameters are meant to be a good representation of the human auditory perception. Predictive models are available to estimate the perception of these quantities. However, calculated psychoacoustic parameters show a lack of accuracy when compared with subjective listening test results for complex and authentic sounds. This paper shows some deficiencies and strengths of conventional algorithms and offers a few ideas for improvement.

Key concepts: Psychoacoustics, Active listening, Computer science, Perception, Speech recognition, Representation (politics), Auditory perception, Algorithm

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