Expressive Speech Synthesis for Urgent Warning Messages Generation in Romani and Slovak

Rusko, Milan; Trnka, Marian; Darjaa, Sakhia; Ritomský, Marian

doi:10.1007/978-3-642-40585-3_33

Cited by 3 publications

(2 citation statements)

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“…In our former research, we experimented with training a stress-predictor [11] on an acted database CRISIS [12], containing utterances with various levels of emotional arousal (calming, neutral, warning and highly insisting). This database was originally designed for expressive speech synthesis purposes.…”

Section: Methodsmentioning

confidence: 99%

Prediction of Stress Level from Speech -- from Database to Regressor

Trnka,

Darjaa,

Sabo

et al. 2023

cai

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The term stress can designate a number of situations and affective reactions. This work focuses on the immediate stress reaction caused by, for example, threat, danger, fear, or great concern. Could measuring stress from speech be a viable fast and non-invasive method? The article describes the development of a system predicting stress from voice -from the creation of the database, and preparation of the training data to the design and tests of the regressor. StressDat, an acted database of speech under stress in Slovak, was designed. After publishing the methodology during its development in [1], this work describes the final form, annotation, and basic acoustic analyses of the data. The utterances presenting various stress-inducing scenarios were acted at three intended stress levels. The annotators used a "stress thermometer" to rate the perceived stress in the utterance on a scale from 0 to 100. Thus, data with a resolution suitable for training the regressor was obtained. Several regressors were trained, tested and compared. On the test-set, the stress estimation works well (R square = 0.72, Concordance Correlation Coefficient = 0.83) but practical application will require much larger volumes of specific training data. StressDat was made publicly available.

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Section: Methodsmentioning

confidence: 99%

Prediction of Stress Level from Speech -- from Database to Regressor

Trnka,

Darjaa,

Sabo

et al. 2023

cai

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“…The EWA-DB speech database is publicly available at ELDA 76 under the name EWA-DB. The database contains 1649 speakers, of which 87 are AD patients, 175 are PD patients, 2 speakers have a combination of AD and PD, 62 are MCI patients and 1323 are healthy controls (HC).…”

Section: Data Recordsmentioning

confidence: 99%

EWA-DB, Slovak Database of Speech Affected by Neurodegenerative Diseases

Rusko,

Sabo,

Trnka

et al. 2023

Preprint

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A new Slovak speech database EWA-DB was created for research purposes aimed at early detection of neurodegenerative diseases from speech. It contains 1649 speakers performing various speech and language tasks, such as sustained vowel phonation, diadochokinesis, naming and picture description. The sample of speakers consists of individuals with Alzheimer’s disease, mild cognitive impairment, Parkinson’s disease, and healthy controls. In this article we describe the EWA-DB development process, the language and speech task selection, patient and healthy control recruitment, as well as the testing and recording protocol. The structure and content of the database and file formats are described in detail. We assume that the presented database could be suitable for the development of automatic systems predicting the diagnoses of Alzheimer’s disease, mild cognitive impairment, and Parkinson’s disease from language and speech features.

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Towards human-machine dialog in Slovak

Ondáš

Juhar

2016

2016 International Conference on Systems, Signals and Image Processing (IWSSIP)

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Expressive Speech Synthesis for Urgent Warning Messages Generation in Romani and Slovak

Cited by 3 publications

References 3 publications

Prediction of Stress Level from Speech -- from Database to Regressor

Prediction of Stress Level from Speech -- from Database to Regressor

EWA-DB, Slovak Database of Speech Affected by Neurodegenerative Diseases

Towards human-machine dialog in Slovak

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