Síntese de nomes em português

Mestrado em Engenharia Electrónica e TelecomunicaçõesPretendeu-se com o trabalho realizado no âmbito desta dissertação desenvolver um sistema capaz de sintetizar nomes em português de forma inteligível. Em termos metodológicos, a opção passou pela utilização de ferramentas de apoio ao desenvolvimento de novas vozes para sistemas de síntese – concretamente o sistema SPICE – e adopção do sistema de síntese Festival. Depois de apresentadas informações de base da área da síntese de voz, assim como informações sobre as funcionalidades dos programas usados neste trabalho (SPICE, MBROLA e Festival), na segunda parte da dissertação, descreveu-se todo o processo prático da criação da voz, fazendo uso do SPICE e MBROLA. O sistema desenvolvido foi avaliado em termos da sua capacidade de efectuar correctamente a conversão grafema-fone e da inteligibilidade dos nomes sintetizados com resultados favoráveis para uma eventual aplicação prática.The major goal of the work presented in this dissertation is to develop a system capable of synthesizing Portuguese names in an intelligible form. In methodological terms the option was to use tools to support the development of new voices to synthesis systems - specifically the SPICE system - and adoption of the synthesis system Festival. After presenting information on the area of speech synthesis as well as information on programs’ features used in this work (SPICE, MBROLA and Festival), the second part of the thesis, describes the practical process of creating a voice using SPICE and MBROLA. The developed system was evaluated in terms of their ability to perform properly the grapheme-phone as well as intelligibility of synthesized names with favorable results for a possible practical application

Statistical morphological disambiguation with application to disambiguation of pronunciations in Turkish /

The statistical morphological disambiguation of agglutinative languages suffers from data sparseness. In this study, we introduce the notion of distinguishing tag sets (DTS) to overcome the problem. The morphological analyses of words are modeled with DTS and the root major part-of-speech tags. The disambiguator based on the introduced representations performs the statistical morphological disambiguation of Turkish with a recall of as high as 95.69 percent. In text-to-speech systems and in developing transcriptions for acoustic speech data, the problem occurs in disambiguating the pronunciation of a token in context, so that the correct pronunciation can be produced or the transcription uses the correct set of phonemes. We apply the morphological disambiguator to this problem of pronunciation disambiguation and achieve 99.54 percent recall with 97.95 percent precision. Most text-to-speech systems perform phrase level accentuation based on content word/function word distinction. This approach seems easy and adequate for some right headed languages such as English but is not suitable for languages such as Turkish. We then use a a heuristic approach to mark up the phrase boundaries based on dependency parsing on a basis of phrase level accentuation for Turkish TTS synthesizers

Name pronunciation in German text-to-speech synthesis

We describe the name analysis and pronunciation component in the German version of the Bell Labs multilingual text-tospeech system. We concentrate on street names because they encompass interest- ing aspects of geographical and personal names. The system was implemented in the framework of finite-state transducer technology, using linguistic criteria as well as frequency distributions derived from a database. In evaluation experiments, we compared the performances of the generalpurpose text analysis and the name-specific system on training and test materials. The name-specific system significantly outperforms the generic system. The error rates compare favorably with results reported in the research literature. Finally, we discuss areas for future work