Издательство Blackwell, 2010, -279 pp.In undergraduate courses that include phonetics, students typically acquire skills both in ear-training and an understanding of the acoustic, physiological, and perceptual characteristics of speech sounds. But there is usually less opportunity to test this knowledge on sizeable quantities of speech data partly because putting together any database that is sufficient in extent to be able to address non-trivial questions in phonetics is very time-consuming. In the last ten years, this issue has been offset somewhat by the rapid growth of national and international speech corpora which has been driven principally by the needs of speech technology. But there is still usually a big gap between the knowledge acquired in phonetics from classes on the one hand and applying this knowledge to available speech corpora with the aim of solving different kinds of theoretical problems on the other. The difficulty stems not just from getting the right data out of the corpus but also in deciding what kinds of graphical and quantitative techniques are available and appropriate for the problem that is to be solved. So one of the main reasons for writing this book is a pedagogical one: it is to bridge this gap between recently acquired knowledge of experimental phonetics on the one hand and practice with quantitative data analysis on the other. The need to bridge this gap is sometimes most acutely felt when embarking for the first time on a larger-scale project, honours or masters thesis in which students collect and analyse their own speech data. But in writing this book, I also have a research audience in mind. In recent years, it has become apparent that quantitative techniques have played an increasingly important role in various branches of linguistics, in particular in laboratory phonology and sociophonetics that sometimes depend on sizeable quantities of speech data labelled at various levels (see e.g., Bod et al, 2003 for a similar view).
This book is something of a departure from most other textbooks on phonetics in at least two ways. Firstly, and as the preceding paragraphs have suggested, I will assume a basic grasp of auditory and acoustic phonetics: that is, I will assume that the reader is familiar with basic terminology in the speech sciences, knows about the international phonetic alphabet, can transcribe speech at broad and narrow levels of detail and has a working knowledge of basic acoustic principles such as the source-filter theory of speech production. All of this has been covered many times in various excellent phonetics texts and the material in e.g., Clark et al. (2005), Johnson (2004), and Ladefoged (1962) provide a firm grounding for such issues that are dealt with in this book. The second way in which this book is somewhat different from others is that it is more of a workbook than a textbook. This is partly again for pedagogical reasons: It is all very well being told (or reading) certain supposed facts about the nature of speech but until you get your hands on real data and test them, they tend to mean very little (and may even be untrue!). So it is for this reason that I have tried to convey something of the sense of data exploration using existing speech corpora, supported where appropriate by exercises. From this point of view, this book is similar in approach to Baayen (in press) and Johnson (2008) who also take a workbook approach based on data exploration and whose analyses are, like those of this book, based on the R computing and programming environment. But this book is also quite different from Baayen (in press) and Johnson (2008) whose main concerns are with statistics whereas mine is with techniques. So our approaches are complementary especially since they all take place in the same programming environment: thus the reader can apply the statistical analyses that are discussed by these authors to many of the data analyses, both acoustic and physiological, that are presented at various stages in this book.
I am also in agreement with Baayen and Johnson about why R is such a good environment for carrying out data exploration of speech: firstly, it is free, secondly it provides excellent graphical facilities, thirdly it has almost every kind of statistical test that a speech researcher is likely to need, all the more so since R is open-source and is used in many other disciplines beyond speech such as economics, medicine, and various other branches of science. Beyond this, R is flexible in allowing the user to write and adapt scripts to whatever kind of analysis is needed, it is very well adapted to manipulating combinations of numerical and symbolic data (and is therefore ideal for a field such as phonetics which is concerned with relating signals to symbols).
Another reason for situating the present book in the R programming environment is because those who have worked on, and contributed to, the Emu speech database project have developed a library of R routines that are customised for various kinds of speech analysis. This development has been ongoing for about 20 years now1 since the time in the late 1980s when Gordon Watson suggested to me during my post-doctoral time at the Centre for Speech Technology Research, Edinburgh University that the S programming environment, a forerunner of R, might be just what we were looking for in querying and analysing speech data and indeed, one or two of the functions that he wrote then, such as the routine for plotting ellipses are still used today.Using speech corpora in phonetics research
Some tools for building and querying labelling speech databases
Applying routines for speech signal processing
Querying annotation structures
An introduction to speech data analysis in R: a study of an EMA database
Analysis of formants and formant transitions
Electropalatography
Spectral analysis.
Classification
