Daniela Braga


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Casa de la Lhéngua: a set of language resources and natural language processing tools for Mirandese
José Pedro Ferreira | Cristiano Chesi | Daan Baldewijns | Fernando Miguel Pinto | Margarita Correia | Daniela Braga | Hyongsil Cho | Amadeu Ferreira | Miguel Dias
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper describes the efforts for the construction of Language Resources and NLP tools for Mirandese, a minority language spoken in North-eastern Portugal, now available on a community-led portal, Casa de la Lhéngua. The resources were developed in the context of a collaborative citizenship project led by Microsoft, in the context of the creation of the first TTS system for Mirandese. Development efforts encompassed the compilation of a corpus with over 1M tokens, the construction of a GTP system, syllable-division, inflection and a Part-of-Speech (POS) tagger modules, leading to the creation of an inflected lexicon of about 200.000 entries with phonetic transcription, detailed POS tagging, syllable division, and stress mark-up. Alongside these tasks, which were made easier through the adaptation and reuse of existing tools for closely related languages, a casting for voice talents among the speaking community was conducted and the first speech database for speech synthesis was recorded for Mirandese. These resources were combined to fulfil the requirements of a well-tested statistical parameter synthesis model, leading to an intelligible voice font. These language resources are available freely at Casa de la Lhéngua, aiming at promoting the development of real-life applications and fostering linguistic research on Mirandese.


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Building High Quality Databases for Minority Languages such as Galician
Francisco Campillo | Daniela Braga | Ana Belén Mourín | Carmen García-Mateo | Pedro Silva | Miguel Sales Dias | Francisco Méndez
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

This paper describes the result of a joint R&D project between Microsoft Portugal and the Signal Theory Group of the University of Vigo (Spain), where a set of language resources was developed with application to Text―to―Speech synthesis. First, a large Corpus of 10000 Galician sentences was designed and recorded by a professional female speaker. Second, a lexicon with phonetic and grammatical information of over 90000 entries was collected and reviewed manually by a linguist expert. And finally, these resources were used for a MOS (Mean Opinion Score) perceptual test to compare two state―of―the―art speech synthesizers of both groups, the one from Microsoft based on HMM, and the one from the University of Vigo based on unit selection.


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Progmatica: A Prosodic Database for European Portuguese
Daniela Braga | Luís Coelho | João P. Teixeira | Diamantino Freitas
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

In this work, a spontaneous speech corpus of broadcasted television material in European Portuguese (EP) is presented. We decided to name it ProGmatica as it is meant to combine prosody information under a pragmatic framework. Our purpose is to analyse, describe and predict the prosodic patterns that are involved in speech acts and discourse events. It is also our goal to relate both prosody and pragmatics to emotion, style and attitude. In future developments, we intend, by this way, to provide EP TTS systems with pragmatic and emotional dimensions. From the whole recorded material we selected, extracted and saved prototypical speech acts with the help of speech analysis tools. We have a multi-speaker corpus, where linguistic, paralinguistic and extra linguistic information are labelled and related to each other. The paper is organized as follows. In section one, a brief state-of-the-art for the available EP corpora containing prosodic information is presented. In section two, we explain the pragmatic criteria used to structure this database. Then, we describe how the speech signal was labelled and which information layers were considered. In section three, we propose a prosodic prediction model to be applied to each speech act in future. In section four, some of the main problems we went through are discussed and future work is presented.