An integrated system for Spanish CSR tasks

This paper presents a new system for the continuous speech recognition of Spanish, integrating previous works in the fields of acoustic-phonetic decoding and language modelling. Acoustic and language models separately trained with speech and text samples, respectivelyare integrated into one single automaton, and their probabilities combined according to a standard beam search procedure. Two key issues were to adequately adjust the beam parameter and the weight affecting the language model probabilities. For the implementation, a client-server arquitecture was selected, due to the desirable working scene where one or more simple machines in the client side make the speech analysis task, and a more powerful workstation in the server side looks for the best sentence hypotheses. Preliminary experimentation gives promising results with around 90% word recognition rates in a medium size word speech recognition task.