Investigating the build-up of precedence effect using reflection masking

The auditory processing level involved in the build‐up of precedence [Freyman et al., J. Acoust. Soc. Am. 90, 874–884 (1991)] has been investigated here by employing reflection masked threshold (RMT) techniques. Given that RMT techniques are generally assumed to address lower levels of the auditory signal processing, such an approach represents a bottom‐up approach to the buildup of precedence. Three conditioner configurations measuring a possible buildup of reflection suppression were compared to the baseline RMT for four reflection delays ranging from 2.5–15 ms. No buildup of reflection suppression was observed for any of the conditioner configurations. Buildup of template (decrease in RMT for two of the conditioners), on the other hand, was found to be delay dependent. For five of six listeners, with reflection delay=2.5 and 15 ms, RMT decreased relative to the baseline. For 5‐ and 10‐ms delay, no change in threshold was observed. It is concluded that the low‐level auditory processing involved in RMT is not sufficient to realize a buildup of reflection suppression. This confirms suggestions that higher level processing is involved in PE buildup. The observed enhancement of reflection detection (RMT) may contribute to active suppression at higher processing levels

Síntesis de voz aplicada a la traducción voz a voz

In the field of speech technologies, text-to-speech conversion is the automatic generation of artificial voices that sound identical to a human voice when reading a text in loud speech. Inside a text-to-speech system, the prosody module produces the prosodic information that is necessary to generate a natural voice: intonational phrases, intonation of the sentence, duration and energy of phonemes, etc. The correct generation of this information directly impacts in the naturalness and expressiveness of the system. The main goals of this thesis is the development of new algorithms to train models for prosody generation that may be used in a text-to-speech system, and their use in the framework of speech-to-speech translation. In this thesis several alternatives were studied for intonation modeling. They combine the parameterization and the intonation model generation as a integrated process. Such approach was successfully judged both with objective and subjective evaluations. The influence of segmental and suprasegmental factors in duration modeling was also studied. Several algorithms were proposed with the results of these studies that may combine segmental and suprasegmental information, likewise other publications of this field. Finally, an analysis of various phrase break models was also performed, both with words and accent groups: classification trees (CART), language modeling (LM) and finite state transducers (FST). The use of the same data set in the experiments was useful to obtain relevant conclusions about the differences between these models. One of the main goals of this thesis was the improvement of naturalness, expressiveness and consistency with the style of the source speaker in text-to-speech systems. This may be done by using the prosody of the source speaker in the framework of speech-to-speech translation as an additional information source. Several algorithms were developed for prosody generation that may integrate such additional information for the prediction of intonation, phoneme duration and phrase breaks. In that direction several approaches were studied to transfer the intonation from one language to the other. The chosen approach was an automatic clustering algorithm that finds a certain number of tonal movements that are related between languages, without any limitation about their number. In this way, it is possible to use this coding for intonation modeling of the target language. Experimental results show an improvement, that is more relevant in close languages, such as Spanish and Catalan. Although no segmental duration transfer was performed between languages, in this thesis is proposed the transfer of rhythm from one language to the other. For that purpose a method that combines the rhythm transfer and audio synchronization was proposed. The synchronizations is included because of its importance for the speech-to-speech translation technology when video is also used. Lastly, in this thesis was also proposed a pause transfer technique in the framework of speech-to-speech translation, by means of alignment information. Studies in training data have shown the advantage of tuples for this task. In order to predict any pause that can not be transferred using the before mentioned method, conventional pause prediction algorithms are used (CART, CART+LM, FST), taking into account the already transferred pauses.Dentro de las tecnologías del habla, la conversión texto a voz consiste en la generación, por medios automáticos, de una voz artificial que genera idéntico sonido al producido por una persona al leer un texto en voz alta. En resumen, los conversores texto a voz son sistemas que permiten la conversión de textos en voz sintética. El proceso de conversión texto a voz se divide en tres módulos básicos: procesamiento del texto, generación de la prosodia y generación de la voz sintética. En el primero de los módulos se realiza la normalización del texto (para expandir abreviaciones, convertir números y fechas en texto, etc), y en ocasiones, luego también se hace un etiquetado morfosintáctico. A continuación se procede a la conversión de los grafemas en fonemas y a la silabificación para obtener la secuencia de fonemas necesaria para reproducir el texto. Posteriormente, el módulo de prosodia genera la información prosódica para poder producir la voz. Para ello se predicen las frases entonativas y la entonación de la oración, y también la duración y la energía de los fonemas, etc. La correcta generación de esta información repercutirá directamente en la naturalidad y expresividad del sistema. En el último modulo de generación de la voz es donde se produce la voz considerando la información provista por los módulos de procesamiento del texto y prosodia. El objetivo de la presente tesis es el desarrollo de nuevos algoritmos para el entrenamiento de modelos de generación de prosodia para la conversión texto a voz, y su aplicación en el marco de la traducción voz a voz. En el caso de los algoritmos de modelado de entonación, en la literatura se proponen generalmente enfoques que incluyen una estilización previa a la parametrización. En esta tesis se estudiaron alternativas para evitar esa estilización, combinando la parametrización y la generación del modelo de entonación en un todo integrado. Dicho enfoque ha resultado exitoso tanto en la evaluación objetiva (usando medidas como el error cuadrático medio o el coeficiente de correlación Pearson) como en la subjetiva. Los evaluadores han considerado que el enfoque propuesto tiene una calidad y una naturalidad superiores a otros algoritmos existentes en la literatura incluidos en las evaluaciones, alcanzando un MOS de naturalidad de 3,55 (4,63 para la voz original) y un MOS de calidad de 3,78 (4,78 para la voz original).Postprint (published version