Abstract: We report in this paper the model adopted by our
system of continuous speech recognition in Arab language SySRA
and the results obtained until now. This system uses the database
Arabdic-10 which is a corpus of word for the Arab language and
which was manually segmented. Phonetic decoding is represented
by an expert system where the knowledge base is translated in the
form of production rules. This expert system transforms a vocal
signal into a phonetic lattice. The higher level of the system takes
care of the recognition of the lattice thus obtained by deferring it in
the form of written sentences (orthographical Form). This level
contains initially the lexical analyzer which is not other than the
module of recognition. We subjected this analyzer to a set of
spectrograms obtained by dictating a score of sentences in Arab
language. The rate of recognition of these sentences is about 70%
which is, to our knowledge, the best result for the recognition of the
Arab language. The test set consists of twenty sentences from four
speakers not having taken part in the training.