Generating Synthetic Pitch Contours Using Prosodic Structure.

This thesis addresses the problem of generating a range of natural sounding pitch contours for speech synthesis to convey the specific meanings of different intonation patterns. Where other models can synthesise intonation adequately for short sentences, longer sentences often sound unnatural as phrasing is only really considered at the sentence level. We build models within a framework of prosodic structure derived from the linguistic analysis of a corpus of speech. We show that the use of appropriate prosodic structure allows us to produce better contours for longer sentences and allows us to capture the original style of the corpus. The resulting model is also sufficiently flexible to be adapted to suitable styles for use in other domains. To convey specific meanings we need to be able to generate different accent types. We find that the infrequency of some accent and boundary types makes them hard to model from the corpus alone. We address this issue by developing a model which allows us to isolate the parameters which control specific accent type shapes, so that we can reestimate these parameters based on other data

An exploration of the rhythm of Malay

In recent years there has been a surge of interest in speech rhythm. However we still lack a clear understanding of the nature of rhythm and rhythmic differences across languages. Various metrics have been proposed as means for measuring rhythm on the phonetic level and making typological comparisons between languages (Ramus et al, 1999; Grabe & Low, 2002; Dellwo, 2006) but the debate is ongoing on the extent to which these metrics capture the rhythmic basis of speech (Arvaniti, 2009; Fletcher, in press). Furthermore, cross linguistic studies of rhythm have covered a relatively small number of languages and research on previously unclassified languages is necessary to fully develop the typology of rhythm. This study examines the rhythmic features of Malay, for which, to date, relatively little work has been carried out on aspects rhythm and timing. The material for the analysis comprised 10 sentences produced by 20 speakers of standard Malay (10 males and 10 females). The recordings were first analysed using rhythm metrics proposed by Ramus et. al (1999) and Grabe & Low (2002). These metrics (∆C, %V, rPVI, nPVI) are based on durational measurements of vocalic and consonantal intervals. The results indicated that Malay clustered with other so-called syllable-timed languages like French and Spanish on the basis of all metrics. However, underlying the overall findings for these metrics there was a large degree of variability in values across speakers and sentences, with some speakers having values in the range typical of stressed-timed languages like English. Further analysis has been carried out in light of Fletcher’s (in press) argument that measurements based on duration do not wholly reflect speech rhythm as there are many other factors that can influence values of consonantal and vocalic intervals, and Arvaniti’s (2009) suggestion that other features of speech should also be considered in description of rhythm to discover what contributes to listeners’ perception of regularity. Spectrographic analysis of the Malay recordings brought to light two parameters that displayed consistency and regularity for all speakers and sentences: the duration of individual vowels and the duration of intervals between intensity minima. This poster presents the results of these investigations and points to connections between the features which seem to be consistently regulated in the timing of Malay connected speech and aspects of Malay phonology. The results are discussed in light of current debate on the descriptions of rhythm

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

A Review of Deep Learning Techniques for Speech Processing

The field of speech processing has undergone a transformative shift with the advent of deep learning. The use of multiple processing layers has enabled the creation of models capable of extracting intricate features from speech data. This development has paved the way for unparalleled advancements in speech recognition, text-to-speech synthesis, automatic speech recognition, and emotion recognition, propelling the performance of these tasks to unprecedented heights. The power of deep learning techniques has opened up new avenues for research and innovation in the field of speech processing, with far-reaching implications for a range of industries and applications. This review paper provides a comprehensive overview of the key deep learning models and their applications in speech-processing tasks. We begin by tracing the evolution of speech processing research, from early approaches, such as MFCC and HMM, to more recent advances in deep learning architectures, such as CNNs, RNNs, transformers, conformers, and diffusion models. We categorize the approaches and compare their strengths and weaknesses for solving speech-processing tasks. Furthermore, we extensively cover various speech-processing tasks, datasets, and benchmarks used in the literature and describe how different deep-learning networks have been utilized to tackle these tasks. Additionally, we discuss the challenges and future directions of deep learning in speech processing, including the need for more parameter-efficient, interpretable models and the potential of deep learning for multimodal speech processing. By examining the field's evolution, comparing and contrasting different approaches, and highlighting future directions and challenges, we hope to inspire further research in this exciting and rapidly advancing field