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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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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. |
format | Online Article Text |
id | pubmed-9163425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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