Phase-Distortion-Robust Voice-Source Analysis

This work concerns itself with the analysis of voiced speech signals, in particular the analysis of the glottal source signal. Following the source-filter theory of speech, the glottal signal is produced by the vibratory behaviour of the vocal folds and is modulated by the resonances of the vocal tract and radiation characteristic of the lips to form the speech signal. As it is thought that the glottal source signal contributes much of the non-linguistic and prosodical information to speech, it is useful to develop techniques which can estimate and parameterise this signal accurately. Because of vocal tract modulation, estimating the glottal source waveform from the speech signal is a blind deconvolution problem which necessarily makes assumptions about the characteristics of both the glottal source and vocal tract. A common assumption is that the glottal signal and/or vocal tract can be approximated by a parametric model. Other assumptions include the causality of the speech signal: the vocal tract is assumed to be a minimum phase system while the glottal source is assumed to exhibit mixed phase characteristics. However, as the literature review within this thesis will show, the error criteria utilised to determine the parameters are not robust to the conditions under which the speech signal is recorded, and are particularly degraded in the common scenario where low frequency phase distortion is introduced. Those that are robust to this type of distortion are not well suited to the analysis of real-world signals. This research proposes a voice-source estimation and parameterisation technique, called the Power-spectrum-based determination of the Rd parameter (PowRd) method. Illustrated by theory and demonstrated by experiment, the new technique is robust to the time placement of the analysis frame and phase issues that are generally encountered during recording. The method assumes that the derivative glottal flow signal is approximated by the transformed Liljencrants-Fant model and that the vocal tract can be represented by an all-pole filter. Unlike many existing glottal source estimation methods, the PowRd method employs a new error criterion to optimise the parameters which is also suitable to determine the optimal vocal-tract filter order. In addition to the issue of glottal source parameterisation, nonlinear phase recording conditions can also adversely affect the results of other speech processing tasks such as the estimation of the instant of glottal closure. In this thesis, a new glottal closing instant estimation algorithm is proposed which incorporates elements from the state-of-the-art techniques and is specifically designed for operation upon speech recorded under nonlinear phase conditions. The new method, called the Fundamental RESidual Search or FRESS algorithm, is shown to estimate the glottal closing instant of voiced speech with superior precision and comparable accuracy as other existing methods over a large database of real speech signals under real and simulated recording conditions. An application of the proposed glottal source parameterisation method and glottal closing instant detection algorithm is a system which can analyse and re-synthesise voiced speech signals. This thesis describes perceptual experiments which show that, iunder linear and nonlinear recording conditions, the system produces synthetic speech which is generally preferred to speech synthesised based upon a state-of-the-art timedomain- based parameterisation technique. In sum, this work represents a movement towards flexible and robust voice-source analysis, with potential for a wide range of applications including speech analysis, modification and synthesis

Methods and studies of laryngeal voice quality analysis in speech production

Voice quality, defined by John Laver as the characteristic auditory colouring of a speaker's voice, is a significant feature of speech, and it is used to signal various properties such as emotions, intentions, and mood of the speaker. While voice quality measurement techniques and algorithms have been developed, much work is needed to obtain a comprehensive view of the function and analysis of human voice in the production of different voice qualities. Two major research questions are presented in this thesis: First, how can the most important laryngeal voice quality features be analyzed, and second, how do the voice quality features affect different facets of vocal expression? To answer these questions, five separate studies of the analysis methodology and two studies regarding the voice quality behaviour were published. The methodology articles describe a voice source analysis software package; a comparison of multiple voice source parameters in breathy, normal, and pressed phonation; a method for evaluating inverse filtering algorithms; comparison of two inverse filtering algorithms; and a method for analyzing intensity regulation of speech. One analysis article studies changes in the laryngeal voice quality when different emotions are expressed in speech and another voice quality changes in expression of prominence in continuous speech. The methodology studies resulted in new tools, methods, and guidelines for voice source analysis, while the analysis studies provide information on how voice quality is used in expressive speech

Voice source characterization for prosodic and spectral manipulation

The objective of this dissertation is to study and develop techniques to decompose the speech signal into its two main components: voice source and vocal tract. Our main efforts are on the glottal pulse analysis and characterization. We want to explore the utility of this model in different areas of speech processing: speech synthesis, voice conversion or emotion detection among others. Thus, we will study different techniques for prosodic and spectral manipulation. One of our requirements is that the methods should be robust enough to work with the large databases typical of speech synthesis. We use a speech production model in which the glottal flow produced by the vibrating vocal folds goes through the vocal (and nasal) tract cavities and its radiated by the lips. Removing the effect of the vocal tract from the speech signal to obtain the glottal pulse is known as inverse filtering. We use a parametric model fo the glottal pulse directly in the source-filter decomposition phase. In order to validate the accuracy of the parametrization algorithm, we designed a synthetic corpus using LF glottal parameters reported in the literature, complemented with our own results from the vowel database. The results show that our method gives satisfactory results in a wide range of glottal configurations and at different levels of SNR. Our method using the whitened residual compared favorably to this reference, achieving high quality ratings (Good-Excellent). Our full parametrized system scored lower than the other two ranking in third place, but still higher than the acceptance threshold (Fair-Good). Next we proposed two methods for prosody modification, one for each of the residual representations explained above. The first method used our full parametrization system and frame interpolation to perform the desired changes in pitch and duration. The second method used resampling on the residual waveform and a frame selection technique to generate a new sequence of frames to be synthesized. The results showed that both methods are rated similarly (Fair-Good) and that more work is needed in order to achieve quality levels similar to the reference methods. As part of this dissertation, we have studied the application of our models in three different areas: voice conversion, voice quality analysis and emotion recognition. We have included our speech production model in a reference voice conversion system, to evaluate the impact of our parametrization in this task. The results showed that the evaluators preferred our method over the original one, rating it with a higher score in the MOS scale. To study the voice quality, we recorded a small database consisting of isolated, sustained Spanish vowels in four different phonations (modal, rough, creaky and falsetto) and were later also used in our study of voice quality. Comparing the results with those reported in the literature, we found them to generally agree with previous findings. Some differences existed, but they could be attributed to the difficulties in comparing voice qualities produced by different speakers. At the same time we conducted experiments in the field of voice quality identification, with very good results. We have also evaluated the performance of an automatic emotion classifier based on GMM using glottal measures. For each emotion, we have trained an specific model using different features, comparing our parametrization to a baseline system using spectral and prosodic characteristics. The results of the test were very satisfactory, showing a relative error reduction of more than 20% with respect to the baseline system. The accuracy of the different emotions detection was also high, improving the results of previously reported works using the same database. Overall, we can conclude that the glottal source parameters extracted using our algorithm have a positive impact in the field of automatic emotion classification

Multi-parametric source-filter separation of speech and prosodic voice restoration

In this thesis, methods and models are developed and presented aiming at the estimation, restoration and transformation of the characteristics of human speech. During a first period of the thesis, a concept was developed that allows restoring prosodic voice features and reconstruct more natural sounding speech from pathological voices using a multi-resolution approach. Inspired from observations with respect to this approach, the necessity of a novel method for the separation of speech into voice source and articulation components emerged in order to improve the perceptive quality of the restored speech signal. This work subsequently represents the main part of this work and therefore is presented first in this thesis. The proposed method is evaluated on synthetic, physically modelled, healthy and pathological speech. A robust, separate representation of source and filter characteristics has applications in areas that go far beyond the reconstruction of alaryngeal speech. It is potentially useful for efficient speech coding, voice biometrics, emotional speech synthesis, remote and/or non-invasive voice disorder diagnosis, etc. A key aspect of the voice restoration method is the reliable separation of the speech signal into voice source and articulation for it is mostly the voice source that requires replacement or enhancement in alaryngeal speech. Observations during the evaluation of above method highlighted that this separation is insufficient with currently known methods. Therefore, the main part of this thesis is concerned with the modelling of voice and vocal tract and the estimation of the respective model parameters. Most methods for joint source filter estimation known today represent a compromise between model complexity, estimation feasibility and estimation efficiency. Typically, single-parametric models are used to represent the source for the sake of tractable optimization or multi-parametric models are estimated using inefficient grid searches over the entire parameter space. The novel method presented in this work proposes advances in the direction of efficiently estimating and fitting multi-parametric source and filter models to healthy and pathological speech signals, resulting in a more reliable estimation of voice source and especially vocal tract coefficients. In particular, the proposed method is exhibits a largely reduced bias in the estimated formant frequencies and bandwidths over a large variety of experimental conditions such as environmental noise, glottal jitter, fundamental frequency, voice types and glottal noise. The methods appears to be especially robust to environmental noise and improves the separation of deterministic voice source components from the articulation. Alaryngeal speakers often have great difficulty at producing intelligible, not to mention prosodic, speech. Despite great efforts and advances in surgical and rehabilitative techniques, currently known methods, devices and modes of speech rehabilitation leave pathological speakers with a lack in the ability to control key aspects of their voice. The proposed multiresolution approach presented at the end of this thesis provides alaryngeal speakers an intuitive manner to increase prosodic features in their speech by reconstructing a more intelligible, more natural and more prosodic voice. The proposed method is entirely non-invasive. Key prosodic cues are reconstructed and enhanced at different temporal scales by inducing additional volatility estimated from other, still intact, speech features. The restored voice source is thus controllable in an intuitive way by the alaryngeal speaker. Despite the above mentioned advantages there is also a weak point of the proposed joint source-filter estimation method to be mentioned. The proposed method exhibits a susceptibility to modelling errors of the glottal source. On the other hand, the proposed estimation framework appears to be well suited for future research on exactly this topic. A logical continuation of this work is the leverage the efficiency and reliability of the proposed method for the development of new, more accurate glottal source models