Statistical prediction of spectral discontinuities of speech in concatenative synthesis

La estimación de discontinuidades espectrales es uno de los mayores problemas en el ámbito de la síntesis concatenativa del habla. Este artículo presenta una metodología basada en el estudio del comportamiento estadístico de medidas objetivas sobre uniones naturales. El objetivo es definir un proceso automático para seleccionar qué medidas emplear como coste de unión para sintetizar un habla lo más natural posible. El artículo presenta los resultados objetivos y subjetivos que permiten validar la propuesta.The estimation of spectral discontinuities is one of the most common problems in speech concatenative synthesis. This paper introduces a methodology based on analyzing the statistical behaviour of objective measures for natural concatenations. The main goal is defining an automatic process capable of including the most appropriate measures as concatenation cost to generate high quality synthetic speech. This paper describes both the objective and subjective results for validating the proposal

New objective distance measures for spectral discontinuities in concatenative speech synthesis

The quality of unit selection based concatenative speech synthesis mainly depends on how well two successive units can be joined together to minimise the audible discontinuities. The objective measure of discontinuity used when selecting units is known as the join cost. The ideal join cost measures perceived discontinuity, based on easily measurable spectral properties of the units being joined, in order to ensure smooth and natural-sounding synthetic speech. In this paper we describe a perceptual experiment conducted to measure the correlation between subjective human perception and various objective spectrally-based measures proposed in the literature. Also we report new objective distance measures derived from various distance metrics based on these spectral features, which have good correlation with human perception to concatenation discontinuities. Our experiments used a state-of-the art unit-selection text-to-speech system: rVoice from Rhetorical Systems Limited

Uma proposta de conversor de texto para voz mesclando concatenação silábica e banco de dados de voz

A evolução natural dos sistemas de informação traz consigo odesenvolvimento e implementação e novas técnicas de interfaceamento com o usuário. Dentre estas novas tecnologias, o Text-to-speech ( texto para voz ) tem tomado uma posição de destaque, por diversos pesquisadores e empresas de grande porte. Este trabalho realiza uma análise de técnicas necessárias ao projeto e implementação de um TTS personalizado, que possibilite um usuário montar seu próprio sistema de TTS

Spectral discontinuity in concatenative speech synthesis – perception, join costs and feature transformations

This thesis explores the problem of determining an objective measure to represent human perception of spectral discontinuity in concatenative speech synthesis. Such measures are used as join costs to quantify the compatibility of speech units for concatenation in unit selection synthesis. No previous study has reported a spectral measure that satisfactorily correlates with human perception of discontinuity. An analysis of the limitations of existing measures and our understanding of the human auditory system were used to guide the strategies adopted to advance a solution to this problem. A listening experiment was conducted using a database of concatenated speech with results indicating the perceived continuity of each concatenation. The results of this experiment were used to correlate proposed measures of spectral continuity with the perceptual results. A number of standard speech parametrisations and distance measures were tested as measures of spectral continuity and analysed to identify their limitations. Time-frequency resolution was found to limit the performance of standard speech parametrisations.As a solution to this problem, measures of continuity based on the wavelet transform were proposed and tested, as wavelets offer superior time-frequency resolution to standard spectral measures. A further limitation of standard speech parametrisations is that they are typically computed from the magnitude spectrum. However, the auditory system combines information relating to the magnitude spectrum, phase spectrum and spectral dynamics. The potential of phase and spectral dynamics as measures of spectral continuity were investigated. One widely adopted approach to detecting discontinuities is to compute the Euclidean distance between feature vectors about the join in concatenated speech. The detection of an auditory event, such as the detection of a discontinuity, involves processing high up the auditory pathway in the central auditory system. The basic Euclidean distance cannot model such behaviour. A study was conducted to investigate feature transformations with sufficient processing complexity to mimic high level auditory processing. Neural networks and principal component analysis were investigated as feature transformations. Wavelet based measures were found to outperform all measures of continuity based on standard speech parametrisations. Phase and spectral dynamics based measures were found to correlate with human perception of discontinuity in the test database, although neither measure was found to contribute a significant increase in performance when combined with standard measures of continuity. Neural network feature transformations were found to significantly outperform all other measures tested in this study, producing correlations with perceptual results in excess of 90%