LANGUAGE MODEL BASED ON THE SPEECH RECOGNITION HISTORY

A small vocabulary pattern recognition system is used for recognizing a sequence of words, such as a sequence of digits (e.g. telephone number) or a sequence of commands. A representation of reference words is stored in a vocabulary 132, 134. Input means 110 are used for receiving a time-sequential input pattern representative of a spoken or written word sequence. A pattern recognizer 120 comprises a word-level matching unit 130 for generating a plurality of possible sequences of words by statistically comparing the input pattern to the representations of the reference words of the vocabulary 132, 134. A cache 150 is used for storing a plurality of most recently recognized words. A sequence-level matching unit 140 selects a word sequence from the plurality of sequences of words in dependence on a statistical language model which provides a probability of a sequence of M words, M≧2. The probability depends on a frequency of occurrence of the sequence in the cache. In this way for many small vocabulary systems where no reliable data is available on frequency of use of word sequences, the cache is used to provide data representative of the actual use.