Disordered Speech Assessment Using Automatic Methods Based on Quantitative Measures

Gu, Lingjia; Harris, John G.; Shrivastav, Rahul

doi:10.1155/asp.2005.1400

Cited by 27 publications

(20 citation statements)

References 12 publications

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“…Comparison-based methods depend on a reference signal or feature prototype of a target word being uttered. In [3], for example, the Itakura-Saito distortion was computed between the produced disordered speech utterance and the same utterance spoken by a healthy individual. In order to account for differences in utterance durations, dynamic time warping was applied.…”

Section: Introductionmentioning

confidence: 99%

Quantifying perturbations in temporal dynamics for automated assessment of spastic dysarthric speech intelligibility

Falk

Hummel

Chan

2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Spastic dysarthric speech is often associated with imprecise placement of articulators which, in turn, cause perturbations in speech temporal dynamics, such as unclear distinctions between adjacent phonemes. While these perturbations can lead to a significant reduction in intelligibility, measures to objectively assess their detrimental effect on intelligibility are lacking. In this paper, short-and long-term temporal dynamics measures are proposed and evaluated as correlates of subjective intelligibility. The former is based on log-energy temporal dynamics information, whereas the latter is based on an auditory-inspired modulation spectral signal representation. A composite measure is also developed based on linearly combining the proposed measures with a tone-unit duration parameter. Experiments with the publicly-available 'Universal Access' database of spastic dysarthric speech show that the proposed composite measure can achieve rank correlations with subjective ratings as high as 0.87, thus providing a tool to automatically diagnose speech disorder severity and to evaluate dysarthria treatment outcomes.

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Section: Introductionmentioning

confidence: 99%

Quantifying perturbations in temporal dynamics for automated assessment of spastic dysarthric speech intelligibility

Falk

Hummel

Chan

2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…The accurate assessment of speech quality is a major research problem that has attracted attention in the field of speech communications for many years. Subjective quality measures given by professional personnel who have received special assessment training are necessarily time consuming and costly (Lingyun Gu et al, 2005).…”

Section: Clinical Solutionmentioning

confidence: 99%

Mobile Systems as a Challenge for Neurological Diseases Management – The Case of Parkinson's Disease

Pastor-Sanz¹,

Pansera²,

Cancela³

et al. 2011

Diagnostics and Rehabilitation of Parkinson's Disease

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“…There have been still few works on automatic speech assessment [9], [10]. Carmichael et al [9] presumed a correlation between probabilistic likelihood scores from HMM-based speech recognition system and the results of intelligibility test from eight listeners in order to formulate the conversion algorithm for intelligibility prediction.…”

Section: Speech Clarity Index (ψ)mentioning

confidence: 99%

“…Carmichael et al [9] presumed a correlation between probabilistic likelihood scores from HMM-based speech recognition system and the results of intelligibility test from eight listeners in order to formulate the conversion algorithm for intelligibility prediction. Lingyun et al [10] applied dynamic time wraping (DTW) and the Itakura-Saito (IS) distortion measure to evaluate the distortion of speech quality by comparing it to healthy speech done by normal speakers. However, both works aimed to measure the difference between disordered speech and normal speech.…”

Section: Speech Clarity Index (ψ)mentioning

confidence: 99%

Speech Clarity Index (.PSI.): A Distance-Based Speech Quality Indicator and Recognition Rate Prediction for Dysarthric Speakers with Cerebral Palsy

Kayasith

Theeramunkong

2009

IEICE Trans. Inf. & Syst.

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SUMMARYIt is a tedious and subjective task to measure severity of a dysarthria by manually evaluating his/her speech using available standard assessment methods based on human perception. This paper presents an automated approach to assess speech quality of a dysarthric speaker with cerebral palsy. With the consideration of two complementary factors, speech consistency and speech distinction, a speech quality indicator called speech clarity index (Ψ) is proposed as a measure of the speaker's ability to produce consistent speech signal for a certain word and distinguished speech signal for different words. As an application, it can be used to assess speech quality and forecast speech recognition rate of speech made by an individual dysarthric speaker before actual exhaustive implementation of an automatic speech recognition system for the speaker. The effectiveness of Ψ as a speech recognition rate predictor is evaluated by rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). The results show that Ψ is a promising indicator for predicting recognition rate of dysarthric speech. All experiments had been done on speech corpus composed of speech data from eight normal speakers and eight dysarthric speakers. key words: speech disorder, dysarthric speech recognition, speech assessment, speech quality index, recognition rate prediction

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Disordered Speech Assessment Using Automatic Methods Based on Quantitative Measures

Cited by 27 publications

References 12 publications

Quantifying perturbations in temporal dynamics for automated assessment of spastic dysarthric speech intelligibility

Quantifying perturbations in temporal dynamics for automated assessment of spastic dysarthric speech intelligibility

Mobile Systems as a Challenge for Neurological Diseases Management – The Case of Parkinson's Disease

Speech Clarity Index (.PSI.): A Distance-Based Speech Quality Indicator and Recognition Rate Prediction for Dysarthric Speakers with Cerebral Palsy

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