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This collection contains behavioural and brain activation data from 3 laboratory studies of speech imitation. Each of the three studies involved behavioural and imaging (MRI) test sessions in which participants were familiarised with novel auditory speech targets, and were asked to imitate them as closely as possible. Across the three studies, there were variations in the type of sounds...
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This database was created through generous funding from The Voice Foundation's Advancing Scientific Voice Research Grant and contains voice samples which have been rated by experienced voice professionals (at least 3 different raters with a minimum of 3 years’ clinical experience) in order to provide educators with standardized materials to better train pre-service clinical voice...
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The increasing availability of magnetic resonance imaging (MRI) as a research, and even clinical, tool in speech production makes possible a wide range of quantitative methods in vocal tract measurement. In these initial stages of application, it is essential that the limits of the method be identified. The present investigation was designed to apply the techniques of digital image analysis...
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There have been considerable research efforts in the area of vocal tract modeling but there is still a small body of information regarding direct 3-D measurements of the vocal tract shape. The purpose of this study was to acquire, using magnetic resonance imaging (MRI), an inventory of speaker-specific, three-dimensional, vocal tract air space shapes that correspond to a particular set of...
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SVQTD (Singing Voice Quality and Technique Database) is a classical tenor singing dataset collected from YouTube, it is mainly used to support supervised machine learning performing paralinguistic singing attribute recognition tasks. In SVQTD, there are nearly 4000 vocal solo segments with $4 - 20$ seconds long, totaling 10.7 hours. These segmenets are partitioned from 400 audios of 6 famous...
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Relationships between a listener's identification of a spoken vowel and its properties as revealed from acoustic measurement of its sound wave have been a subject of study by many investigators. Both the utterance and the identification of a vowel depend upon the language and dialectal backgrounds and the vocal and auditory characteristics of the individuals concerned. The purpose of this...
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This paper presents a large-scale study of subglottal resonances (SGRs) (the resonant frequencies of the tracheo-bronchial tree) and their relations to various acoustical and physiological characteristics of speakers. The paper presents data from a corpus of simultaneous microphone and accelerometer recordings of consonant-vowel-consonant (CVC) words embedded in a carrier phrase spoken by 25...
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The frequencies, magnitudes, and bandwidths of vocal tract resonances are all important in understanding and synthesizing speech. High precision acoustic impedance spectra of the vocal tracts of 10 subjects were measured from 10 Hz to 4.2 kHz by injecting a broadband acoustic signal through the lips. Between 300 Hz and 4 kHz the acoustic resonances R (impedance minima measured through the...
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See also tools at https://github.com/rsprouse/xray_microbeam_database
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A dataset of ultrasound and audio recorded with children with speech sound disorders. The Ultrax 2020 dataset is a collection of ultrasound tongue imaging and audio data, gathered from children with speech sound disorders by speech and language therapists in hospital environments. We recorded data with 43 English-speaking children, but only 37 gave consent to share their data. These are 11...
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A dataset of ultrasound and audio recorded with children with cleft lip and palate The cleft dataset is a collection of ultrasound tongue imaging and audio data, gathered from children with cleft lip and palate by a research speech and language therapist working in a hospital environment. We recorded data with 39 English-speaking children, but only 29 gave consent to share their data. These...
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A dataset of ultrasound and audio recordings from children with speech sound disorders. The UltraPhonix dataset contains 20 speakers (16 male, 4 female), aged 6-13 years.
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A dataset of ultrasound and audio recordings from children with speech sound disorders. The UXSSD dataset contains 8 speakers (2 female and 6 male), aged 5-10 years.
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