Advances in Speech and Language Technologies for Iberian by Juan Luis Navarro Mesa, Alfonso Ortega, António Teixeira,

By Juan Luis Navarro Mesa, Alfonso Ortega, António Teixeira, Eduardo Hernández Pérez, Pedro Quintana Morales, Antonio Ravelo García, Iván Guerra Moreno, Doroteo T. Toledano (eds.)

This publication constitutes the refereed lawsuits of the IberSPEECH 2014 convention, held in Las Palmas de Gran Canaria, Spain, in November 19-21, 2014. The 29 papers offered have been conscientiously reviewed and chosen from 60 submissions. The papers are equipped in topical sections on speech construction, research, coding and synthesis; speaker and language characterization; automated speech acceptance; speech of language applied sciences in numerous software fields.

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Additional resources for Advances in Speech and Language Technologies for Iberian Languages: Second International Conference, IberSPEECH 2014, Las Palmas de Gran Canaria, Spain, November 19-21, 2014. Proceedings

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In addition, visually impaired users cannot benefit from subtitles. In these cases, it would be much more convenient to be able to listen to the lecturer in the user’s own language. A text-to-speech (TTS) synthesizer is a system capable of generating an artificial speech track for a given text. State-of-the-art TTS systems usually employ one of two approaches: unit selection [11] or statistical parametric speech synthesis [34]. The TTS system presented here is based on the latter, as it is usually regarded as the most reliable synthesis approach when it comes to intelligibility [12], which is a key factor in our problem.

If we compute separate average scores for each group (see Fig. 4), the observed trends are found to be consistent and almost opposite. For some listeners (Fig. 4a), two-period windows produce clearly better synthetic speech, especially for the female voice. For some others (Fig. 4b), there are no differences between analysis configurations for the female voice, while longer windows are clearly preferred for the male voice. We investigated the causes of this dichotomy and we concluded that each group of listeners was penalizing different aspects of quality.

28–29 (2009) 2. : Modeling and interpolation of Austrian German and Viennese dialect in HMM-based speech synthesis. Speech Communication 52(2), 164–179 (2010) 3. : HMM-based Tianjin Dialect speech synthesis using bilateral question Set. In: 2011 IEEE International Workshop on Machine Learning for Signal Processing, Beijing, pp. 1–4 (2011) 4. : Synthesis of dialect speech for an underresourced language. In: SATNAC, Western Cape (2012) 5. : Simultaneous modeling of spectrum, pitch and duration in HMMbased speech synthesis.

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