Wikispeech - a content management system for speech databases

Draxler, Christoph; Jänsch, Klaus

doi:10.21437/interspeech.2008-457

Cited by 12 publications

(8 citation statements)

References 1 publication

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“…This may be a bold statement, but semantic interoperability is not the problem, it's the data format level interoperability in combination with disagreement on the extent of a global data model. Thus, a common minimal core data model encompassing the concept of a corpus is needed, and this data model must be supported by all tools - [6,8] are first examples of how this ambitious goal can be reached. In the future we need to go even further.…”

Section: Discussionmentioning

confidence: 99%

“…Some tools provide import-and export functions, but significant amounts of data conversion and reformatting is still necessary. A global data model for the speech processing workflow, based on the concept of a corpus, has been proposed by [6]. Such a data model will be immediately useful for webbased and collaborative work, but transformation costs, both in terms of converting data and in terms of adapting software to access data in the global data model, are high.…”

Section: Workflowmentioning

confidence: 99%

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Speech processing tools - an introduction to interoperability

Draxler

Altosaar²,

Furui

et al. 2011

Interspeech 2011

Self Cite

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Section: Discussionmentioning

confidence: 99%

Section: Workflowmentioning

confidence: 99%

Speech processing tools - an introduction to interoperability

Draxler

Altosaar²,

Furui

et al. 2011

Interspeech 2011

Self Cite

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“…The target words and sentences were visually presented in Dutch orthography on a computer screen using SpeechRecorder [10], and participants were instructed to read them aloud as naturally as possible. Trials were presented in a pseudorandomized order, ensuring that the two members of the same word pair were at least 62 trials apart.…”

Section: Methodsmentioning

confidence: 99%

“…The recordings were automatically forced aligned using the WebMAUS Basic tool [10], which segmented the target words and vowels. These were subsequently manually checked by six researchers.…”

Section: Acoustic Measurementsmentioning

confidence: 99%

Acoustic correlates of Dutch lexical stress re-examined: Spectral tilt is not always more reliable than intensity

Severijnen¹,

Bosker²,

McQueen³

2022

Speech Prosody 2022

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The present study examined two acoustic cues in the production of lexical stress in Dutch: spectral tilt and overall intensity. Sluijter and Van Heuven (1996) reported that spectral tilt is a more reliable cue to stress than intensity. However, that study included only a small number of talkers (10) and only syllables with the vowels /aː/ and /ɔ/.The present study re-examined this issue in a larger and more variable dataset. We recorded 38 native speakers of Dutch (20 females) producing 744 tokens of Dutch segmentally overlapping words (e.g., VOORnaam vs. voorNAAM, "first name" vs. "respectable"), targeting 10 different vowels, in variable sentence contexts. For each syllable, we measured overall intensity and spectral tilt following Sluijter and Van Heuven (1996).Results from Linear Discriminant Analyses showed that, for the vowel /aː/ alone, spectral tilt showed an advantage over intensity, as evidenced by higher stressed/unstressed syllable classification accuracy scores for spectral tilt. However, when all vowels were included in the analysis, the advantage disappeared.These findings confirm that spectral tilt plays a larger role in signaling stress in Dutch /aː/ but show that, for a larger sample of Dutch vowels, overall intensity and spectral tilt are equally important.

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“…Recordings took place in quiet rooms using an AKG condenser microphone and USB external soundcard (PreSonus), with a sampling rate of 44100 Hz. The image was presented on the computer screen with software system SpeechRecorder (Draxler & Jänsch, 2017). The participants were seated at a table and the microphone was adjusted to each participant and positioned at an approximately 15-20 cm distance from the mouth.…”

Section: Corpus and Recording Protocolmentioning

confidence: 99%

Age and gender effects in European Portuguese spontaneous speech

Albuquerque

Valente

Teixeira

et al. 2021

loquens

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Aging is part of the normal evolution of human beings. However, the knowledge about speech in the older ages is still dispersed and incomplete. Considering conflicting findings reported in prior research, this study aims to contribute to increase our knowledge about age effects on the spontaneous speech of Portuguese adults. In order to analyze the effects of age on rhythmic, intonation and voice quality domains, several parameters were extracted from spontaneous speech produced by 112 adults, aged between 35 and 97. Data were obtained through a picture description task. The results showed that the most consistent age-related effects are an increase in speech pauses, mainly in men, and a Harmonics-to-Noise Ratio (HNR) decrease in women. Speaking fundamental frequency (f0) tends to decrease in women and to slightly increase in men with age. These findings for Portuguese are in line with previous research suggesting that suprasegmental characteristics of speech change with age, with some gender differences.

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Wikispeech - a content management system for speech databases

Cited by 12 publications

References 1 publication

Speech processing tools - an introduction to interoperability

Speech processing tools - an introduction to interoperability

Acoustic correlates of Dutch lexical stress re-examined: Spectral tilt is not always more reliable than intensity

Age and gender effects in European Portuguese spontaneous speech

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