\documentclass{llncs}
\usepackage{makeidx}
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\begin{document}
\mainmatter              % start of the contributions
\title{Recording and Annotation \\*of the Czech Speech Corpus}
\author{Vlasta Radov\'a and Josef Psutka}
\institute{University of West Bohemia, Department of Cybernetics,\\
  Univerzitn\'\i\ 22, 306 14 Plze\v{n}, Czech Republic\\
  \email{radova@kky.zcu.cz, psutka@kky.zcu.cz}}
\maketitle
\begin{abstract}
  The  paper reassumes  our papers presented
at the previous TSD workshops (\cite{62ref2}, \cite{62ref3}) and
concerns the Czech speech corpus which is being developed at the
Department of Cybernetics, University of West Bohemia in Pilsen.
It describes procedures of the corpus recording and annotation.
\end{abstract}

\section{Introduction}
The Czech speech corpus described in this paper is being developed
at the Department of Cybernetics at the University of West Bohemia
in Pilsen since 1998. The purpose of the corpus is to provide
enough speech data for training of Czech continuous speech
recognition systems. Our goal is to collect the corpus containing
speech of at least 100 speakers, each of them is asked to read a
set of 150 sentences. The texts to be read are selected from 3
Czech newspapers and have to satisfy several requirements that
were specified in \cite{62ref3}.

For the recording of  the corpus a special program was developed
that allows to record each utterance by two different microphones
simultaneously. The function as well as the interface of the
recording program is described in Section 2.

Before the utterances can be used for training of  a speech
recognition system they have to be annotated. The annotation is a
process during that the speech data are divided into segments and
various non-speech events (like lip smack, throat clear etc.) and
various kinds of noise (e.g. chair squeak, door slam) are
indicated in the utterances. In our corpus, the segments are
defined as such parts of the utterance that contain either a whole
sentence or some of the specified non-speech events. Since the
non-speech events can be either isolated (it means no speech
co-occurs with such an event) or they can co-occur with the
speech, several types of descriptors were used to mark the place
where the events occurred in the speech. The process  of the
corpus annotation is described in Section~3.


\section{Recording of the Corpus}
The corpus is recorded in an office room where no person but the
speaker is present during the recording. However there is
  some
noise from neighbouring offices in the recording room.

In order to record the corpus we developed a special recording
program \emph{Vlny} that allows to record the corpus sentence by
sentence. Each sentence is recorded by two microphones
simultaneously. One of the microphones is a close-talking
microphone yielding utterances of a very high quality. The other
one is a desk microphone that records utterances with a common
office noise. Such an arrangement enables to yield two identical
utterances that differs only in the amount of noise that they
contain.

 At the beginning of the recording
session each speaker obtains some instructions. The instructions
provide a general introduction to the project and a description of
the task. The speakers are asked to read each sentence over before
they utter and record it. They are also instructed to speak
naturally and clearly in their usual accent at normal loudness.
Each speaker is given a short demonstration how to operate the
recording program.

\begin{figure}[!b]
  \centering
  \includegraphics[width=10cm]{fig1.eps}
  \caption{A typical window of the recording program \emph{Vlny}.}\label{62fig1}
\end{figure}
The actual recording process consists of several steps, each
co-ordinated by clicking on screen buttons. A typical window that
appears after a sentence is recorded is given in Figure
\ref{62fig1}. At the top of the window there is the sentence that
has just been read. Below it there are two windows each of them
contains a figure of the signal from a microphone. The left window
is for the close-talking microphone, the right window is for the
desk microphone. The speaker has the possibility to check that the
recording from any microphone is satisfactory by clicking on the
corresponding \emph{Play} button. Below the signal window there is
also a scale window for each microphone. It shows the level of the
signal at the input to the computer. The optimal level is
approximately 50\% and it should be adjusted by a supervisor
during the demonstration phase, using a pre-amplifier for each
microphone separately. During the actual recording it is not
allowed to change the settings of the pre-amplifiers any more.
However when the level of the signal in any microphone decreases
below 10\% or increases above 90\% the speaker is asked by the
program to read the sentence once more in a more or less loud
voice respectively. Similarly, when either the silence between
clicking on the \emph{Start} button and the beginning of the
utterance, or the silence between the end of an utterance and
clicking on the \emph{Stop} button is shorter than 0.5 s the
speaker is asked to repeat the sentence once more. Besides this,
the speaker has a possibility to repeat the sentence on the base
of his/her own decision by clicking on the \emph{Repeat sentence}
button. The \emph{Previous sentence} button gives to the speakers
a chance to go back to the previous sentence, the \emph{Next
sentence} button moves the speaker to the next sentence. The
actual recording of a sentence is controlled by the \emph{Start}
and \emph{Stop} buttons that appear after the \emph{Next sentence}
button is pressed.

\section{Annotation of the Corpus}
During the annotation process each utterance is transcribed in the
form how it was really pronounced. It means with mispronunciation,
unintelligible pronunciation, various non-speech events and
various kinds of noise, if they occurred during the utterance. The
rules that we use for the annotation of the corpus are as follows:
\begin{itemize}
  \item[$\bullet$] Non-speech events and noises are indicated by a descriptor
   enclosed in square brackets. The descriptors contain only capitalized
   alphabetic characters and underscores and are drawn from the list in Table \ref{62tab1}.
\begin{table}
  \centering
 \begin{tabular}{p{4cm} p{4cm}}
  % after \\ : \hline or \cline{col1-col2} \cline{col3-col4} ...
  AH             & LOUD\_BREATH\\
  COUGH          & PAPER\_RUSTLE\\
  DOOR\_SLAM     & SIGH \\
  GRUNT          & TONGUE\_CLICK\\
  LIP\_SMACK     & UNINTELLIGIBLE\\
  MM             & MOUSE\_CLICK\\
  PHONE\_RING    & MIKE\_OVERLOAD\\
  THROAT\_CLEAR  & REMOTE\_ENGINE\\
  UH             & NOISE\\
  UM             & KNOCK\_ON\_MIC\\
  CHAIR\_SQUEAK  & MUSIC\\
  CROSS\_TALK    & BACKGROUND\_MUSIC\\
  ER             & SIGNAL\_MISSING\\
  LAUGHTER       & SILENCE \\
  \\
\end{tabular}
 \caption{List of the descriptors of non-speech events and kinds
of noise.}\label{62tab1}
\end{table}
  \item[$\bullet$] The descriptor is placed at the point at which the non-speech
   event occurred.

   E.g.: \emph{Sd\v{e}lil to ministr \v{s}kolstv\'\i\ [THROAT\_CLEAR] Jan Sokol.}
  \item[$\bullet$]If a non-speech event overlaps a spoken lexical item the
   descriptor is placed close to the item that co-occurred with and the
   character "$<$" or "$>$" is appended to the descriptor depending on
   whether the description is placed right or left of the co-occurring lexical
   item.

   E.g.: \emph{Akcie Komer\v{c}n\'\i\ banky [CHAIR\_SQUEAK$>$]
    pom\v{e}rn\v{e} z\v{r}eteln\v{e} oslabily.}

   Or:  \emph{Akcie Komer\v{c}n\'\i\ banky pom\v{e}rn\v{e}
    [$<$CHAIR\_SQUEAK] z\v{r}eteln\v{e} oslabily.}

   Both alternatives are equivalent and mean that a chair squeaked
   during the pronouncing of the word \emph{pom\v{e}rn\v{e}}.
  \item[$\bullet$]If a non-speech event overlaps with more than one lexical
   item the character "/" is appended to the descriptor and the
   descriptor is then used like brackets bounding the lexical
   items.

   E.g.: \emph{Nab\'{\i}dka [NOISE/] udr\v{z}ela ceny ust\'{a}len\'{e}. [/NOISE]}
  \item[$\bullet$]If the waveform is truncated (e.g. due to a recording
   error by the system) the symbol "$\sim$" is used to mark the incompletely spoken sentence:

   E.g.: \emph{Spole\v{c}nost bude z rozhodnut\'\i\ vl\'{a}dy nejprve $\sim$}
  \item[$\bullet$]Mispronounced but intelligible words are bounded with the mark
   "*". For example if the prompt was \emph{P\v{r}edsedov\'{e} stran se domluvili}
   and the speaker has read \emph{P\v{r}edsedov\'{e} stran se domlouvili} the
   utterance is transcribed as \emph{P\v{r}edsedov\'{e} stran se *domlouvili*}.
  \item[$\bullet$]Unintelligible words are replaced by the
  non-speech event [UNINTELLIGIBLE].

\end{itemize}
\begin{figure}[!b]
  \centering
  \includegraphics[width=10cm]{fig2.eps}
  \caption{A typical window of the \emph{Transcriber}.}\label{62fig2}
\end{figure}
For annotation of all utterances we use \emph{Transcriber}, a very
useful tool for segmenting, labelling and transcribing speech
\cite{62ref1}. It was developed in France and is freely available
at \texttt{http://www.etca.fr/CTA/gip/Projets/Transcriber/}.
A~typical window of that tool is given in Figure \ref{62fig2}. The
upper part of the window is basically a text editor that allows to
type the transcription of the utterances. Besides this the speaker
of the utterance can be specified here. At the bottom part of the
window the speech signal is depicted.


\section{Conclusion}
The paper deals with the Czech speech corpus that is being
developed at the Department of Cybernetics of the University of
West Bohemia in Pilsen. It reassumes our papers presented at
previous TSD workshops, where some questions about the corpus
design were discussed \cite{62ref2} and algorithms for sentences
selection \cite{62ref3} were described. The presented paper
concerns with two next problems -- utterances recording and corpus
annotation.

\section{Acknowledgements}The work was supported
 by the Ministry of Education of the Czech Republic, project no. VS97159,
  and by the Grant Agency of the Czech Republic, project no. 102/96/K087.

\begin{thebibliography}{3}
\bibitem{62ref1} Barras C. at all: Transcriber: a Free Tool for Segmenting,
 Labeling and Transcribing Speech. In: First International Conference on
 Language Resources and Evaluation (LREC) (1998)
\bibitem{62ref2}Radov\'a, V.: Design of the Czech Speech Corpus for Speech
 Recognition Applications with a Large Vocabulary. In: Sojka, P.,
 Matou\v{s}ek, V., Pala, K., Kope\v{c}ek, I. (eds.): Text, Speech, Dialogue.
 Proc. of the First Workshop on Text, Speech, Dialogue. Brno, Czech Republic
 (1998) 299--304
\bibitem{62ref3}Radov\'a, V.,  Vop\'alka, P.: Methods of Sentences Selection
 for Read-Speech Corpus Design. In: Matou\v{s}ek, V. at all (eds.): Text,
 Speech and Dialogue. Proc. of the Second Workshop on Text, Speech, Dialogue.
 Springer-Verlag, Berlin Heidelberg (1999) 165--170
\end{thebibliography}
\end{document}
