NEURONAL NETWORKS AND SELF-ORGANIZING MAPS - NEW COMPUTER TECHNIQUES IN THE ACOUSTIC EVALUATION OF THE INFANT CRY

Neuronal networks are computer-based techniques for the evaluation and control of complex information systems and processes. So far, they ha ve been used in engineering, telecommunications, artificial speech and speech recognition. A new approach in neuronal network is the self-or ganizing map (Kohonen map). In the phase of 'learning', the map adapts to the patterns of the primary signals. If, in the phase of 'using th e map', the input signal hits the field of the primary signals, it res embles them and is called a 'winner'. In our study, we recorded the cr ies of newborns and young infants using digital audio tape (DAT) and a high quality microphone. The cries were elicited by tactile stimuli w earing headphones. In 27 cases, delayed auditory feedback was presente d to the children using a headphone and an additional three-head tape- recorder. Spectrographic characteristics of the cries were classified by 20-step bark spectra and then applied to the neuronal networks. It was possible to recognize similarities of different cries of the same children as well as interindividual differences, which are also audibl e to experienced listeners. Differences were obvious in profound heari ng loss. We know much about the cries of both healthy and sick infants , but a reliable investigation regimen, which can be used for clinical routine purposes, has yet not been developed. If, in the future, it b ecomes possible to classify spectrographic characteristics automatical ly, even if they are not audible, neuronal networks may be helpful in the early diagnosis of infant diseases.