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The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features

The LaMIT database consists in recordings of 100 Italian sentences. The sentences in the database were designed so to include all phonemes of the Italian language, and also take into account the typical frequency of each phoneme in written Italian. Four native adult speakers of Standard Italian, rai...

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Autores principales: Di Benedetto, Maria-Gabriella, Shattuck-Hufnagel, Stefanie, Choi, Jeung-Yoon, De Nardis, Luca, Arango, Javier, Chan, Ian, DeCaprio, Alec, Budoni, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163425/
https://www.ncbi.nlm.nih.gov/pubmed/35669006
http://dx.doi.org/10.1016/j.dib.2022.108275
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author Di Benedetto, Maria-Gabriella
Shattuck-Hufnagel, Stefanie
Choi, Jeung-Yoon
De Nardis, Luca
Arango, Javier
Chan, Ian
DeCaprio, Alec
Budoni, Sara
author_facet Di Benedetto, Maria-Gabriella
Shattuck-Hufnagel, Stefanie
Choi, Jeung-Yoon
De Nardis, Luca
Arango, Javier
Chan, Ian
DeCaprio, Alec
Budoni, Sara
author_sort Di Benedetto, Maria-Gabriella
collection PubMed
description The LaMIT database consists in recordings of 100 Italian sentences. The sentences in the database were designed so to include all phonemes of the Italian language, and also take into account the typical frequency of each phoneme in written Italian. Four native adult speakers of Standard Italian, raised and living in Rome, Italy, two female and two male, pronounced the sentences in two different recording sessions; two repetitions for each sentence per speaker were therefore collected, for a total of 800 recordings. The database was specifically created for application in the LaMIT project, that focuses on the application to the Italian language of the Lexical Access model proposed by Ken Stevens for American English. The model relies on the detection of specific acoustic discontinuities called landmarks and other acoustic cues to features that characterize each phoneme. Each recording was thus processed to generate a set of labeling files that identify both predicted landmarks and other cues, and actual landmarks/cues. The labeling files, compiled according to the labeling syntax used in the Praat speech processing software, are also made available as part of the LAMIT database.
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spelling pubmed-91634252022-06-05 The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features Di Benedetto, Maria-Gabriella Shattuck-Hufnagel, Stefanie Choi, Jeung-Yoon De Nardis, Luca Arango, Javier Chan, Ian DeCaprio, Alec Budoni, Sara Data Brief Data Article The LaMIT database consists in recordings of 100 Italian sentences. The sentences in the database were designed so to include all phonemes of the Italian language, and also take into account the typical frequency of each phoneme in written Italian. Four native adult speakers of Standard Italian, raised and living in Rome, Italy, two female and two male, pronounced the sentences in two different recording sessions; two repetitions for each sentence per speaker were therefore collected, for a total of 800 recordings. The database was specifically created for application in the LaMIT project, that focuses on the application to the Italian language of the Lexical Access model proposed by Ken Stevens for American English. The model relies on the detection of specific acoustic discontinuities called landmarks and other acoustic cues to features that characterize each phoneme. Each recording was thus processed to generate a set of labeling files that identify both predicted landmarks and other cues, and actual landmarks/cues. The labeling files, compiled according to the labeling syntax used in the Praat speech processing software, are also made available as part of the LAMIT database. Elsevier 2022-05-16 /pmc/articles/PMC9163425/ /pubmed/35669006 http://dx.doi.org/10.1016/j.dib.2022.108275 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Di Benedetto, Maria-Gabriella
Shattuck-Hufnagel, Stefanie
Choi, Jeung-Yoon
De Nardis, Luca
Arango, Javier
Chan, Ian
DeCaprio, Alec
Budoni, Sara
The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title_full The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title_fullStr The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title_full_unstemmed The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title_short The LaMIT database: A read speech corpus for acoustic studies of the Italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
title_sort lamit database: a read speech corpus for acoustic studies of the italian language toward lexical access based on the detection of landmarks and other acoustic cues to features
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163425/
https://www.ncbi.nlm.nih.gov/pubmed/35669006
http://dx.doi.org/10.1016/j.dib.2022.108275
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