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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