On the Computation of the Kullback-Leibler Measure for Spectral Distances

Efficient algorithms for the exact and approximate computation of the symmetrical Kullback-Leibler (1998) measure for spectral distances are presented for linear predictive coding (LPC) spectra. A interpretation of this measure is given in terms of the poles of the spectra. The performances of the algorithms in terms of accuracy and computational complexity are assessed for the application of computing concatenation costs in unit-selection-based speech synthesis. With the same complexity and storage requirements, the exact method is superior in terms of accuracy

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

Prediction and Realisation of Conversational Characteristics by Utilising Spontaneous Speech for Unit Selection

Unit selection speech synthesis has reached high levels of naturalness and intelligibility for neutral read aloud speech. However, synthetic speech generated using neutral read aloud data lacks all the attitude, intention and spontaneity associated with everyday conversations. Unit selection is heavily data dependent and thus in order to simulate human conversational speech, or create synthetic voices for believable virtual characters, we need to utilise speech data with examples of how people talk rather than how people read. In this paper we included carefully selected utterances from spontaneous conversational speech in a unit selection voice. Using this voice and by automatically predicting type and placement of lexical fillers and filled pauses we can synthesise utterances with conversational characteristics. A perceptual listening test showed that it is possible to make synthetic speech sound more conversational without degrading naturalness

Two unit selection singing synthesisers

Two speech synthesisers were adapted for singing synthesis using unit selection techniques provided by the Festival speech synthesis system. A limited domain approach was used by focussing on the pitch, duration and word of each note. The first synthesiser used the cluster unit technique on a database of an octave range, where each note had a specific word assigned to it. Some of the automatic techniques used (e.g. for segmentation) were designed for speech and should ideally be adapted to take account of the differences between singing and speaking. Better quality was achieved with a multisyn engine and improved database design. This database used a smaller pitch range and only three syllables, ’la’ ’ti’ and ’so’, but each syllable could be synthesised on any available note, and in any combination of notes and syllables. This was achieved by weighting the target cost of selecting units from the database in favour of choosing units with the correct pitch and duration. Finally, prosodic modification was applied to units in the multisyn engine, but this degraded quality as a result of how the units were modified. Although the quality of synthesis was appropriate for the intended applications, the database was small and linguistic structure simple. To build a larger scale singing synthesiser, either some aspect of the database should be kept simple, such as vocabulary, or prosodic modification of units should be improved through further analysis of the characteristics of singing

Synthesis and Evaluation of Conversational Characteristics in Speech Synthesis

Conventional synthetic voices can synthesise neutral read aloud speech well. But, to make synthetic speech more suitable for a wider range of applications, the voices need to express more than just the word identity. We need to develop voices that can partake in a conversation and express, e.g. agreement, disagreement, hesitation, in a natural and believable manner. In speech synthesis there are currently two dominating frameworks: unit selection and HMM-based speech synthesis. Both frameworks utilise recordings of human speech to build synthetic voices. Despite the fact that the content of the recordings determines the segmental and prosodic phenomena that can be synthesised, surprisingly little research has been made on utilising the corpus to extend the limited behaviour of conventional synthetic voices. In this thesis we will show how natural sounding conversational characteristics can be added to both unit selection and HMM-based synthetic voices, by adding speech from a spontaneous conversation to the voices. We recorded a spontaneous conversation, and by manually transcribing and selecting utterances we obtained approximately two thousand utterances from it. These conversational utterances were rich in conversational speech phenomena, but they lacked the general coverage that allows unit selection and HMM-based synthesis techniques to synthesise high quality speech. Therefore we investigated a number of blending approaches in the synthetic voices, where the conversational utterances were augmented with conventional read aloud speech. The synthetic voices that contained conversational speech were contrasted with conventional voices without conversational speech. The perceptual evaluations showed that the conversational voices were generally perceived by listeners as having a more conversational style than the conventional voices. This conversational style was largely due to the conversational voices’ ability to synthesise utterances that contained conversational speech phenomena in a more natural manner than the conventional voices. Additionally, we conducted an experiment that showed that natural sounding conversational characteristics in synthetic speech can convey pragmatic information, in our case an impression of certainty or uncertainty, about a topic to a listener. The conclusion drawn is that the limited behaviour of conventional synthetic voices can be enriched by utilising conversational speech in both unit selection and HMM-based speech synthesis

Conveying expressivity and vocal effort transformation in synthetic speech with Harmonic plus Noise Models

Aquesta tesi s'ha dut a terme dins del Grup en de Tecnologies Mèdia (GTM) de l'Escola d'Enginyeria i Arquitectura la Salle. El grup te una llarga trajectòria dins del cap de la síntesi de veu i fins i tot disposa d'un sistema propi de síntesi per concatenació d'unitats (US-TTS) que permet sintetitzar diferents estils expressius usant múltiples corpus. De forma que per a realitzar una síntesi agressiva, el sistema usa el corpus de l'estil agressiu, i per a realitzar una síntesi sensual, usa el corpus de l'estil corresponent. Aquesta tesi pretén proposar modificacions del esquema del US-TTS que permetin millorar la flexibilitat del sistema per sintetitzar múltiples expressivitats usant només un únic corpus d'estil neutre. L'enfoc seguit en aquesta tesi es basa en l'ús de tècniques de processament digital del senyal (DSP) per aplicar modificacions de senyal a la veu sintetitzada per tal que aquesta expressi l'estil de parla desitjat. Per tal de dur a terme aquestes modificacions de senyal s'han usat els models harmònic més soroll per la seva flexibilitat a l'hora de realitzar modificacions de senyal. La qualitat de la veu (VoQ) juga un paper important en els diferents estils expressius. És per això que es va estudiar la síntesi de diferents emocions mitjançant la modificació de paràmetres de VoQ de baix nivell. D'aquest estudi es van identificar un conjunt de limitacions que van donar lloc als objectius d'aquesta tesi, entre ells el trobar un paràmetre amb gran impacte sobre els estils expressius. Per aquest fet l'esforç vocal (VE) es va escollir per el seu paper important en la parla expressiva. Primer es va estudiar la possibilitat de transferir l'VE entre dues realitzacions amb diferent VE de la mateixa paraula basant-se en la tècnica de predicció lineal adaptativa del filtre de pre-èmfasi (APLP). La proposta va permetre transferir l'VE correctament però presentava limitacions per a poder generar nivells intermitjos d'VE. Amb la finalitat de millorar la flexibilitat i control de l'VE expressat a la veu sintetitzada, es va proposar un nou model d'VE basat en polinomis lineals. Aquesta proposta va permetre transferir l'VE entre dues paraules qualsevols i sintetitzar nous nivells d'VE diferents dels disponibles al corpus. Aquesta flexibilitat esta alineada amb l'objectiu general d'aquesta tesi, permetre als sistemes US-TTS sintetitzar diferents estils expressius a partir d'un únic corpus d'estil neutre. La proposta realitzada també inclou un paràmetre que permet controlar fàcilment el nivell d'VE sintetitzat. Això obre moltes possibilitats per controlar fàcilment el procés de síntesi tal i com es va fer al projecte CreaVeu usant interfícies gràfiques simples i intuïtives, també realitzat dins del grup GTM. Aquesta memòria conclou presentant el treball realitzat en aquesta tesi i amb una proposta de modificació de l'esquema d'un sistema US-TTS per incloure els blocs de DSP desenvolupats en aquesta tesi que permetin al sistema sintetitzar múltiple nivells d'VE a partir d'un corpus d'estil neutre. Això obre moltes possibilitats per generar interfícies d'usuari que permetin controlar fàcilment el procés de síntesi, tal i com es va fer al projecte CreaVeu, també realitzat dins del grup GTM. Aquesta memòria conclou presentant el treball realitzat en aquesta tesi i amb una proposta de modificació de l'esquema del sistema US-TTS per incloure els blocs de DSP desenvolupats en aquesta tesi que permetin al sistema sintetitzar múltiple nivells d'VE a partir d'un corpus d'estil neutre.Esta tesis se llevó a cabo en el Grup en Tecnologies Mèdia de la Escuela de Ingeniería y Arquitectura la Salle. El grupo lleva una larga trayectoria dentro del campo de la síntesis de voz y cuenta con su propio sistema de síntesis por concatenación de unidades (US-TTS). El sistema permite sintetizar múltiples estilos expresivos mediante el uso de corpus específicos para cada estilo expresivo. De este modo, para realizar una síntesis agresiva, el sistema usa el corpus de este estilo, y para un estilo sensual, usa otro corpus específico para ese estilo. La presente tesis aborda el problema con un enfoque distinto proponiendo cambios en el esquema del sistema con el fin de mejorar la flexibilidad para sintetizar múltiples estilos expresivos a partir de un único corpus de estilo de habla neutro. El planteamiento seguido en esta tesis esta basado en el uso de técnicas de procesamiento de señales (DSP) para llevar a cabo modificaciones del señal de voz para que este exprese el estilo de habla deseado. Para llevar acabo las modificaciones de la señal de voz se han usado los modelos harmónico más ruido (HNM) por su flexibilidad para efectuar modificaciones de señales. La cualidad de la voz (VoQ) juega un papel importante en diferentes estilos expresivos. Por ello se exploró la síntesis expresiva basada en modificaciones de parámetros de bajo nivel de la VoQ. Durante este estudio se detectaron diferentes problemas que dieron pié a los objetivos planteados en esta tesis, entre ellos el encontrar un único parámetro con fuerte influencia en la expresividad. El parámetro seleccionado fue el esfuerzo vocal (VE) por su importante papel a la hora de expresar diferentes emociones. Las primeras pruebas se realizaron con el fin de transferir el VE entre dos realizaciones con diferente grado de VE de la misma palabra usando una metodología basada en un proceso filtrado de pre-émfasis adaptativo con coeficientes de predicción lineales (APLP). Esta primera aproximación logró transferir el nivel de VE entre dos realizaciones de la misma palabra, sin embargo el proceso presentaba limitaciones para generar niveles de esfuerzo vocal intermedios. A fin de mejorar la flexibilidad y el control del sistema para expresar diferentes niveles de VE, se planteó un nuevo modelo de VE basado en polinomios lineales. Este modelo permitió transferir el VE entre dos palabras diferentes e incluso generar nuevos niveles no presentes en el corpus usado para la síntesis. Esta flexibilidad está alineada con el objetivo general de esta tesis de permitir a un sistema US-TTS expresar múltiples estilos de habla expresivos a partir de un único corpus de estilo neutro. Además, la metodología propuesta incorpora un parámetro que permite de forma sencilla controlar el nivel de VE expresado en la voz sintetizada. Esto abre la posibilidad de controlar fácilmente el proceso de síntesis tal y como se hizo en el proyecto CreaVeu usando interfaces simples e intuitivas, también realizado dentro del grupo GTM. Esta memoria concluye con una revisión del trabajo realizado en esta tesis y con una propuesta de modificación de un esquema de US-TTS para expresar diferentes niveles de VE a partir de un único corpus neutro.This thesis was conducted in the Grup en Tecnologies M`edia (GTM) from Escola d’Enginyeria i Arquitectura la Salle. The group has a long trajectory in the speech synthesis field and has developed their own Unit-Selection Text-To-Speech (US-TTS) which is able to convey multiple expressive styles using multiple expressive corpora, one for each expressive style. Thus, in order to convey aggressive speech, the US-TTS uses an aggressive corpus, whereas for a sensual speech style, the system uses a sensual corpus. Unlike that approach, this dissertation aims to present a new schema for enhancing the flexibility of the US-TTS system for performing multiple expressive styles using a single neutral corpus. The approach followed in this dissertation is based on applying Digital Signal Processing (DSP) techniques for carrying out speech modifications in order to synthesize the desired expressive style. For conducting the speech modifications the Harmonics plus Noise Model (HNM) was chosen for its flexibility in conducting signal modifications. Voice Quality (VoQ) has been proven to play an important role in different expressive styles. Thus, low-level VoQ acoustic parameters were explored for conveying multiple emotions. This raised several problems setting new objectives for the rest of the thesis, among them finding a single parameter with strong impact on the expressive style conveyed. Vocal Effort (VE) was selected for conducting expressive speech style modifications due to its salient role in expressive speech. The first approach working with VE was based on transferring VE between two parallel utterances based on the Adaptive Pre-emphasis Linear Prediction (APLP) technique. This approach allowed transferring VE but the model presented certain restrictions regarding its flexibility for generating new intermediate VE levels. Aiming to improve the flexibility and control of the conveyed VE, a new approach using polynomial model for modelling VE was presented. This model not only allowed transferring VE levels between two different utterances, but also allowed to generate other VE levels than those present in the speech corpus. This is aligned with the general goal of this thesis, allowing US-TTS systems to convey multiple expressive styles with a single neutral corpus. Moreover, the proposed methodology introduces a parameter for controlling the degree of VE in the synthesized speech signal. This opens new possibilities for controlling the synthesis process such as the one in the CreaVeu project using a simple and intuitive graphical interfaces, also conducted in the GTM group. The dissertation concludes with a review of the conducted work and a proposal for schema modifications within a US-TTS system for introducing the VE modification blocks designed in this dissertation

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%

Overcoming the limitations of statistical parametric speech synthesis

At the time of beginning this thesis, statistical parametric speech synthesis (SPSS) using hidden Markov models (HMMs) was the dominant synthesis paradigm within the research community. SPSS systems are effective at generalising across the linguistic contexts present in training data to account for inevitable unseen linguistic contexts at synthesis-time, making these systems flexible and their performance stable. However HMM synthesis suffers from a ‘ceiling effect’ in the naturalness achieved, meaning that, despite great progress, the speech output is rarely confused for natural speech. There are many hypotheses for the causes of reduced synthesis quality, and subsequent required improvements, for HMM speech synthesis in literature. However, until this thesis, these hypothesised causes were rarely tested. This thesis makes two types of contributions to the field of speech synthesis; each of these appears in a separate part of the thesis. Part I introduces a methodology for testing hypothesised causes of limited quality within HMM speech synthesis systems. This investigation aims to identify what causes these systems to fall short of natural speech. Part II uses the findings from Part I of the thesis to make informed improvements to speech synthesis. The usual approach taken to improve synthesis systems is to attribute reduced synthesis quality to a hypothesised cause. A new system is then constructed with the aim of removing that hypothesised cause. However this is typically done without prior testing to verify the hypothesised cause of reduced quality. As such, even if improvements in synthesis quality are observed, there is no knowledge of whether a real underlying issue has been fixed or if a more minor issue has been fixed. In contrast, I perform a wide range of perceptual tests in Part I of the thesis to discover what the real underlying causes of reduced quality in HMM synthesis are and the level to which they contribute. Using the knowledge gained in Part I of the thesis, Part II then looks to make improvements to synthesis quality. Two well-motivated improvements to standard HMM synthesis are investigated. The first of these improvements follows on from averaging across differing linguistic contexts being identified as a major contributing factor to reduced synthesis quality. This is a practice typically performed during decision tree regression in HMM synthesis. Therefore a system which removes averaging across differing linguistic contexts and instead performs averaging only across matching linguistic contexts (called rich-context synthesis) is investigated. The second of the motivated improvements follows the finding that the parametrisation (i.e., vocoding) of speech, standard practice in SPSS, introduces a noticeable drop in quality before any modelling is even performed. Therefore the hybrid synthesis paradigm is investigated. These systems aim to remove the effect of vocoding by using SPSS to inform the selection of units in a unit selection system. Both of the motivated improvements applied in Part II are found to make significant gains in synthesis quality, demonstrating the benefit of performing the style of perceptual testing conducted in the thesis