Analysis and Calibration of Lombard Effect and Whisper for Speaker Recognition.

Variations in vocal effort can create challenges for speaker recognition systems that are optimized for use with neutral speech. The Lombard effect and whisper are two commonly-occurring forms of vocal effort variation that result in non-neutral speech, the first due to noise exposure and the second due to intentional adjustment on the part of the speaker. In this article, a comparative evaluation of speaker recognition performance in non-neutral conditions is presented using multiple Lombard effect and whisper corpora. The detrimental impact of these vocal effort variations on discrimination and calibration performance on global, per-corpus, and per-speaker levels is explored using conventional error metrics, along with visual representations of the model and score spaces. A non-neutral speech detector is subsequently introduced and used to inform score calibration in several ways. Two calibration approaches are proposed and shown to reduce error to the same level as an optimal calibration approach that relies on ground-truth vocal effort information. This article contributes a generalizable methodology towards detecting vocal effort variation and using this knowledge to inform and advance speaker recognition system behavior.

Effects of cognitive impairment on prosodic parameters of speech production planning in multiple sclerosis.

Cognitive impairment (CI) affects 40-65% of patients with multiple sclerosis (MS). CI can have a negative impact on a patient's everyday activities, such as engaging in conversations. Speech production planning ability is crucial for successful verbal interactions and thus for preserving social and occupational skills. This study investigates the effect of cognitive-linguistic demand and CI on speech production planning in MS, as reflected in speech prosody. A secondary aim is to explore the clinical potential of prosodic features for the prediction of an individual's cognitive status in MS. A total of 45 subjects, that is 22 healthy controls (HC) and 23 patients in early stages of relapsing-remitting MS, underwent neuropsychological tests probing specific cognitive processes involved in speech production planning. All subjects also performed a read speech task, in which they had to read isolated sentences manipulated as for phonological length. Results show that the speech of MS patients with CI is mainly affected at the temporal level (articulation and speech rate, pause duration). Regression analyses further indicate that rate measures are correlated with working memory scores. In addition, linear discriminant analysis shows the ROC AUC of identifying MS patients with CI is 0.70 (95% confidence interval: 0.68-0.73). Our findings indicate that prosodic planning is deficient in patients with MS-CI and that the scope of planning depends on patients' cognitive abilities. We discuss how speech-based approaches could be used as an ecological method for the assessment and monitoring of CI in MS.

Changes in Speech Chunking in Reading Aloud is a Marker of Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease.

BACKGROUND: Speech and Language Impairments, generally attributed to lexico-semantic deficits, have been documented in Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). This study investigates the temporal organisation of speech (reflective of speech production planning) in reading aloud in relation to cognitive impairment, particularly working memory and attention deficits in MCI and AD. The discriminative ability of temporal features extracted from a newly designed read speech task is also evaluated for the detection of MCI and AD. METHOD: Sixteen patients with MCI, eighteen patients with mild-to-moderate AD and thirty-six healthy controls (HC) underwent a battery of neuropsychological tests and read a set of sentences varying in cognitive load, probed by manipulating sentence length and syntactic complexity. RESULTS: Our results show that Mild-to-Moderate AD is associated with a general slowness of speech, attributed to a higher number of speech chunks, silent pauses and dysfluences, and slower speech and articulation rates. Speech chunking in the context of high cognitive-linguistic demand appears to be an informative marker of MCI, specifically related to early deficits in working memory and attention. In addition, Linear Discriminant Analysis shows the ROC AUCs (Areas Under the Receiver Operating Characteristic Curves) of identifying MCI vs. HC, MCI vs. AD and AD vs. HC using these speech characteristics are 0.75, 0.90 and 0.94 respectively. CONCLUSION: The implementation of connected speech-based technologies in clinical and community settings may provide additional information for the early detection of MCI and AD.