Reliability and Clinical Relevance of Segmental Analysis Based on Intelligibility Assessment

Nuffelen, Gwen Van; Bodt, Marc De; Guns, Cindy; Wuyts, Floris; Heyning, Paul Van de

doi:10.1159/000153433

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…In more detail, these target phonemes were transcribed in the presence of the remaining phonemes of a word (e.g., transcribing target phoneme 'n' in 'nit' which was presented as '.it'). All three criterion measures were shown to be reliable and valid (Van Nuffelen et al, 2008;Xue et al, 2021b).…”

Section: Discussionmentioning

confidence: 93%

Assessing speech intelligibility of pathological speech in sentences and word lists: The contribution of phoneme-level measures

Xue

Hout

Cucchiarini

et al. 2023

Journal of Communication Disorders

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Section: Discussionmentioning

confidence: 93%

Assessing speech intelligibility of pathological speech in sentences and word lists: The contribution of phoneme-level measures

Xue

Hout

Cucchiarini

et al. 2023

Journal of Communication Disorders

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“…The perceptual intelligibility score is calculated as the percentage of correctly identified phonemes. Previous research [4,15] has demonstrated that the intelligibility scores derived from the DIA are highly reliable (an interrater correlation of 0.91 and an intrarater correlation of 0.93 [15]).…”

Section: Perceptual Test and Evaluation Databasementioning

confidence: 99%

Automated Intelligibility Assessment of Pathological Speech Using Phonological Features

Middag

Martens

Nuffelen

et al. 2009

EURASIP J. Adv. Signal Process.

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It is commonly acknowledged that word or phoneme intelligibility is an important criterion in the assessment of the communication efficiency of a pathological speaker. People have therefore put a lot of effort in the design of perceptual intelligibility rating tests. These tests usually have the drawback that they employ unnatural speech material (e.g., nonsense words) and that they cannot fully exclude errors due to listener bias. Therefore, there is a growing interest in the application of objective automatic speech recognition technology to automate the intelligibility assessment. Current research is headed towards the design of automated methods which can be shown to produce ratings that correspond well with those emerging from a well-designed and well-performed perceptual test. In this paper, a novel methodology that is built on previous work (Middag et al., 2008) is presented. It utilizes phonological features, automatic speech alignment based on acoustic models that were trained on normal speech, context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples. The experimental evaluation of the new system reveals that the root mean squared error of the discrepancies between perceived and computed intelligibilities can be as low as 8 on a scale of 0 to 100.

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“…The perceptual intelligibility score is calculated as the percentage of correctly identified phonemes. Previous research [2,6] showed that the intelligibility scores derived from the DIA are highly reliable (an intraclass correlation of 0.93 and an interclass correlation of 0.91 [6]).…”

Section: Subjective Evaluation and Databasementioning

confidence: 99%

Objective intelligibility assessment of pathological speakers

et al. 2008

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Intelligibility is a primary measure for the assessment of pathological speech. Traditionally, it is measured using a perceptual test, which is by definition subjective in nature. Consequently, there is a great interest in reliable, automatic and therefore objective methods. This paper presents such a method that incorporates an automatic speech recognizer (ASR) for producing features that characterize the pronunciations of a speaker and an intelligibility prediction model (IPM) for converting these features into an intelligibility score. High correlations (about 0.90) between objective and perceptual scores are obtained with a system comprising two different speech recognizers: one with traditional acoustic models relating acoustical observations to triphone states and one using phonological features as an intermediate layer between the acoustical observations and the phonetic states.

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Reliability and Clinical Relevance of Segmental Analysis Based on Intelligibility Assessment

Cited by 7 publications

References 9 publications

Assessing speech intelligibility of pathological speech in sentences and word lists: The contribution of phoneme-level measures

Assessing speech intelligibility of pathological speech in sentences and word lists: The contribution of phoneme-level measures

Automated Intelligibility Assessment of Pathological Speech Using Phonological Features

Objective intelligibility assessment of pathological speakers

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