CORAA ASR: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese.
Automatic Speech recognition (ASR) is a complex and challenging task. In recent years, there have been significant advances in the area. In particular, for the Brazilian Portuguese (BP) language, there were around 376 h publicly available for the ASR task until the second half of 2020. With the rele...
| Publicado en: | Language Resources & Evaluation Vol. 57; no. 3; pp. 1139 - 1172 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Sep2023
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=170029257&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 170029257 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Sep2023 vid: 57 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 170029257 10.1007/s10579-022-09621-4 ppf: 1139 ppct: 33 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1MB tig: atl: CORAA ASR: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese. aug: au: Candido Junior, Arnaldo Casanova, Edresson Soares, Anderson de Oliveira, Frederico Santos Oliveira, Lucas Junior, Ricardo Corso Fernandes da Silva, Daniel Peixoto Pinto Fayet, Fernando Gorgulho Carlotto, Bruno Baldissera Gris, Lucas Rafael Stefanel Aluísio, Sandra Maria affil: São Paulo State University, São José do Rio Preto, Brazil Instituto de Ciências Matemáticas e de Computação - University of São Paulo, São Carlos, Brazil Federal University of Goias, Goiânia, Brazil Federal University of Technology — Paraná (UTFPR), Medianeira, Brazil su: Automatic speech recognition Speech Portuguese language Speech perception Corpora Freedom of speech Error rates sug: subj: Automatic speech recognition Speech Portuguese language Speech perception Corpora Freedom of speech Error rates keyword: Brazilian Portuguese Prepared speech Public datasets Public speech corpora Spontaneous speech ab: Automatic Speech recognition (ASR) is a complex and challenging task. In recent years, there have been significant advances in the area. In particular, for the Brazilian Portuguese (BP) language, there were around 376 h publicly available for the ASR task until the second half of 2020. With the release of new datasets in early 2021, this number increased to 574 h. The existing resources, however, are composed of audios containing only read and prepared speech. There is a lack of datasets including spontaneous speech, which are essential in several ASR applications. This paper presents CORAA (Corpus of Annotated Audios) ASR with 290 h, a publicly available dataset for ASR in BP containing validated pairs of audio-transcription. CORAA ASR also contains European Portuguese audios (4.6 h). We also present a public ASR model based on Wav2Vec 2.0 XLSR-53, fine-tuned over CORAA ASR. Our model achieved a Word Error Rate (WER) of 24.18% on CORAA ASR test set and 20.08% on Common Voice test set. When measuring the Character Error Rate (CER), we obtained 11.02% and 6.34% for CORAA ASR and Common Voice, respectively. CORAA ASR corpora were assembled to both improve ASR models in BP with phenomena from spontaneous speech and motivate young researchers to start their studies on ASR for Portuguese. All the corpora are publicly available at https://github.com/nilc-nlp/CORAA under the CC BY-NC-ND 4.0 license. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2023. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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