A cochlear implant (CI) is the most suitable option for individuals with severe profound hearing loss. CI restores the audibility to near perfection and offers good speech understanding in quiet. However, the speech perception in noise with CIs is less optimal as most speech coding strategies of CIs encode only the temporal envelope. Besides the current CI signal coding strategies lacks sophisticated pre-processing. In the current study, we proposed a novel pre-processing method to improve speech Intelligibility in noise and tested using the acoustic simulations of cochlear implants. The proposed noise reduction technique aims to minimize the mean square error (MSE) between the temporal envelopes of the enhanced speech and its clean speech. Therefore, the proposed method will be suitable for CI applications. This paper provides an analysis of the theoretical derivation of the noise suppression function and also the performance evaluation using objective and subjective tests. The effectiveness of the proposed method was objectively evaluated using the SRMR-CI and ESTOI. Additionally, speech recognition through the acoustic simulations of the cochlear implant was done for the subjective evaluation. Performance of the proposed method was compared with the Weiner filter (WF) and sigmoidal functions. The sinewave vocoder was used to simulate the cochlear implant perception. Both objective and subjective scores revealed that the performance of the proposed technique is superior to the WF and sigmoidal function.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)
- Electrical and Electronic Engineering