Predicting Hearing Aid Gain Values for Enhancing the Speech Intelligibility Using Correlation Algorithm

The tranquil solution for the hearing impaired subjects to get rid of the impairment is to wear the appropriate hearing aid to increase the hearing level and clarity of the perceived speech. Though the present day hearing aids are inbuilt with a suitable noise removing algorithm to get a clear speech signal, the satisfaction among the users is low. The satisfaction of the hearing aid users will be enhanced only with the fixation of appropriate Real Ear Insertion Gain (REIG) values for different frequency bands of the perceived speech signal. Various prescriptive procedures were developed so far in prescribing these values. But, the strenuous task for the audiologists is in selecting the best procedure and to suggest required modifications. The present work focuses this problem faced by the audiologists by analyzing the various technical snags and arrived with suitable solutions. In the present work, an expert system was developed to predict gain values without the need of the prescriptive procedures and reduced the trial and error time of the audiologists. A gain suggestion database of the satisfied subjects was developed, and later it was used by the correlation algorithm in the gain prediction process. The successful gain suggestions of the most correlated subject for different frequencies in the database are recommended for the new subject. The developed expert system was validated by performing hearing aid trials with 256 hearing impaired subjects and 93.7% of them received satisfaction. The successful gain suggestions made by the expert system are stored continuously to strengthen the database, so as to recommend the most appropriate gain values for the new subject.