BABEL: an Eastern European multi-language database

Roach, Peter J.; Arnfield, Simon; Barry, William J.; Baltova, J.; Boldea, M.; Fourcin, Adrian; Gonet, W.; Gubrynowicz, Ryszard; Hallum, E.; Lamel, Lori; Marasek, Krzysztof; Marchal, A.; Meister, Einar; Vicsi, Klára

doi:10.1109/icslp.1996.608002

Cited by 29 publications

(17 citation statements)

References 2 publications

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“…This allowed us to take both free and bound functors into account, better reflecting adult speakers' full-fledged (but, of course, implicit) knowledge of their native grammar. The corpora were phonologically transcribed to provide a more realistic signal using phonotypical pronunciations in a semi-automated manner (Roach et al, 1996). …”

Section: Methodsmentioning

confidence: 99%

Word frequency cues word order in adults: cross-linguistic evidence

Gervain¹,

Sebastián‐Gallés²,

Díaz³

et al. 2013

Front. Psychol.

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One universal feature of human languages is the division between grammatical functors and content words. From a learnability point of view, functors might provide entry points or anchors into the syntactic structure of utterances due to their high frequency. Despite its potentially universal scope, this hypothesis has not yet been tested on typologically different languages and on populations of different ages. Here we report a corpus study and an artificial grammar learning experiment testing the anchoring hypothesis in Basque, Japanese, French, and Italian adults. We show that adults are sensitive to the distribution of functors in their native language and use them when learning new linguistic material. However, compared to infants' performance on a similar task, adults exhibit a slightly different behavior, matching the frequency distributions of their native language more closely than infants do. This finding bears on the issue of the continuity of language learning mechanisms.

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Section: Methodsmentioning

confidence: 99%

Word frequency cues word order in adults: cross-linguistic evidence

Gervain¹,

Sebastián‐Gallés²,

Díaz³

et al. 2013

Front. Psychol.

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“…The material used for current experiments was taken from the BABEL Hungarian language speech database (Roach et al, 1996). BABEL is a read speech database, involving 60 non-trained speakers' data.…”

Section: Methodsmentioning

confidence: 99%

“…According to Vicsi-Szaszák (2010), the training of the acoustic-prosodic models of the prosodic segmenter was performed on a part of the Hungarian database BABEL (Roach et al, 1996), hand-labelled initially for phonological phrases based primarily on the F0 contour, but also on the annotators' perception of phonological-phrase-initial stress after listening to the utterance. 1600 utterances from 32 speakers were used to train 11 state left-to-right Hidden Markov Models for each phonological phrase + silence presented in Table 1.…”

Section: Training Of the Prosodic Segmentermentioning

confidence: 99%

Exploiting Prosody for Syntactic Analysis in Automatic Speech Understanding

Szaszák

Beke

2012

JLM

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Keywords : prosody, syntax, phonological phrase, boundary detection The relation between syntax and prosody is evident, even if the prosodic structure cannot be directly mapped to the syntactic one and vice versa. Syntax-to-prosody mapping is widely used in text-tospeech applications, but prosody-to-syntax mapping is mostly missing from automatic speech recognition/understanding systems. This paper presents an experiment towards filling this gap and evaluating whether a HMM-based automatic prosodic segmentation tool can be used to support the reconstruction of the syntactic structure directly from speech. Results show that up to 85% of syntactic clause boundaries and up to about 70% of embedded syntactic phrase boundaries could be identified based on the detection of phonological phrases. Recall rates do not depend further on syntactic layering, in other words, whether the phrase is multiply embedded or not. Clause boundaries can be well assigned to intonational phrase level in read speech and can be well separated from lower level syntactic phrases based on the type of the aligned phonological phrase(s). These findings can be exploited in speech understanding systems, allowing for the recovery of the skeleton of the syntactic structure, based purely on the speech signal.

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“…Az első oszlop a feltételt tar talmazza, az itt szereplő hangnak követnie kell a vizsgált hangot. (A táblázatokban a beszédhangok jelölésére SAMPA-szimbólumokat használunk (Roach et al 1996), a szövegben szintúgy, de a hangjelét ekkor szögletes zárójelbe tettük. A magyar beszédhangok SAMPA jelölésrendszerét lásd a függelékben.…”

Section: Az Adott Beszédhangot Megelőző Hangok Kiejtésének Vizsgálataunclassified

A verbális tanári instrukciók az osztálytermi diskurzusban III.

Molnár¹

2016

Anyanyelv-pedagógia

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BABEL: an Eastern European multi-language database

Cited by 29 publications

References 2 publications

Word frequency cues word order in adults: cross-linguistic evidence

Word frequency cues word order in adults: cross-linguistic evidence

Exploiting Prosody for Syntactic Analysis in Automatic Speech Understanding

A verbális tanári instrukciók az osztálytermi diskurzusban III.

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