Intelligibility as a linear combination of dimensions in dysarthric speech

Bodt, Marc De; Huici, Maria Esperanza Hernandez-Diaz; Heyning, Paul Van de

doi:10.1016/s0021-9924(02)00065-5

Cited by 159 publications

(103 citation statements)

References 15 publications

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“…Haan, 1977), however other dimensions include vowel dispersion (Bond & Moore, 1994) and gender (Bradlow, Torretta, & Pisoni, 1996), to name only a few. Although intelligibility is often assessed with the dependent measure of accuracy (or error) rates, one may just as easily use a subjective rating scale to assess intelligibility (e.g., Clarke, 1960;De Bodt, Hernandez-Diaz-Huici, & Van De Heyning, 2002;Metz & Schiavetti, 1994;Tye-Murray, Barkmeier, & Folkins, 1991). It is important not to confuse the construct with the measurement; intelligibility does not necessarily equal accurate identification.…”

Section: Discussionmentioning

confidence: 99%

Naturalistic and Experimental Analyses of Word Frequency and Neighborhood Density Effects in Slips of the Ear

Vitevitch

2002

Lang Speech

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A comparison of the lexical characteristics of 88 auditory misperceptions (i.e., slips of the ear) showed no difference in word-frequency, neighborhood density, and neighborhood frequency between the actual and the perceived utterances. Another comparison of slip of the ear tokens (i.e., actual and perceived utterances) and words in general (i.e., randomly selected from the lexicon) showed that slip of the ear tokens had denser neighborhoods and higher neighborhood frequency than words in general, as predicted from laboratory studies. Contrary to prediction, slip of the ear tokens were higher in frequency of occurrence than words in general. Additional laboratory-based investigations examined the possible source of the contradictory word frequency finding, highlighting the importance of using naturalistic and experimental data to develop models of spoken language processing.

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Section: Discussionmentioning

confidence: 99%

Naturalistic and Experimental Analyses of Word Frequency and Neighborhood Density Effects in Slips of the Ear

Vitevitch

2002

Lang Speech

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“…De Bodt et al [29] concluded that resonance, in addition to voice, prosody and, in particular, articulation can influence the intelligibility in dysartric speech. As the above described resonance deviations are rather mild in most of the cases, it is necessary to explore further whether they will have a harmful effect on the overall speech intelligibility of hearing impaired children.…”

Section: N Baudonck Et Al / International Journal Of Pediatric Otormentioning

confidence: 99%

Nasalance and nasality in children with cochlear implants and children with hearing aids

Baudonck

Lierde

D’haeseleer

et al. 2015

International Journal of Pediatric Otorhinolaryngology

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“…According to the outcomes of the efficacy tests presented in [9], user satisfaction towards such a system appears to be quite high. However, most of these systems are not yet capable of automatically detecting problems at the level of individual speech sounds, which are known to have an impact on speech intelligibility [10][11][12][13][14]. Our goal is to develop more robust acoustic models for pathological speech and incorporate automatic speech recognition (ASR) technology to detect these problems.…”

Section: Introductionmentioning

confidence: 99%

Multi-Stage DNN Training for Automatic Recognition of Dysarthric Speech

Yılmaz¹,

Ganzeboom²,

Cucchiarini³

et al. 2017

Interspeech 2017

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Incorporating automatic speech recognition (ASR) in individualized speech training applications is becoming more viable thanks to the improved generalization capabilities of neural network-based acoustic models. The main problem in developing applications for dysarthric speech is the relative in-domain data scarcity. Collecting representative amounts of dysarthric speech data is difficult due to rigorous ethical and medical permission requirements, problems in accessing patients who are generally vulnerable and often subject to altering health conditions and, last but not least, the high variability in speech resulting from different pathological conditions. Developing such applications is even more challenging for languages which in general have fewer resources, fewer speakers and, consequently, also fewer patients than English, as in the case of a mid-sized language like Dutch. In this paper, we investigate a multi-stage deep neural network (DNN) training scheme aimed at obtaining better modeling of dysarthric speech by using only a small amount of in-domain training data. The results show that the system employing the proposed training scheme considerably improves the recognition of Dutch dysarthric speech compared to a baseline system with single-stage training only on a large amount of normal speech or a small amount of in-domain data.

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Intelligibility as a linear combination of dimensions in dysarthric speech

Cited by 159 publications

References 15 publications

Naturalistic and Experimental Analyses of Word Frequency and Neighborhood Density Effects in Slips of the Ear

Naturalistic and Experimental Analyses of Word Frequency and Neighborhood Density Effects in Slips of the Ear

Nasalance and nasality in children with cochlear implants and children with hearing aids

Multi-Stage DNN Training for Automatic Recognition of Dysarthric Speech

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