Subspace and envelope subtraction algorithms for noise reduction in cochlear implants

Abstract

The performance of two noise reduction algorithms is evaluated using 14 subjects fitted with the Clarion S-Series and Clarion I1 implant devices. The first algorithm, based on signal subspace principles, is used for preprocessing sentences embedded in +5 dB noise. The second algorithm is based on the subtraction of the noisy speech envelopes from an estimate of the noise envelopes. The noise envelopes are estimated continuously using a variation of the minimum statistics algorithm. Results showed that the subspace algorithm produced significant improvements in sentence recognition scores compared to the subjects' daily strategy. Small improvements were also obtained for a few subjects with the envelope subtraction algorithm.

Speech Processing in Vocoder-Centric Cochlear Implants

“…Ideally, noise reduction algorithms should be easy to implement and be integrated into the existing coding strategies. Only a few algorithms [100,101] were proposed along this direction.…”

“…Toledo et al [100] proposed a simple envelope subtraction algorithm based on the principle that the clean (noise-free) envelope can be estimated by simply subtracting the noisy envelope from the noise envelope. This approach requires estimate of the noise envelope, which can be obtained using a noise estimation algorithm -an algorithm that continuously tracks the noise envelope even during speech activity.…”

Companding to improve cochlear-implant speech recognition in speech-shaped noise

“…To compensate for the impaired ability to understand speech in noise, many noise suppression algorithms have been proposed for cochlear implants ͑Hamacher et al, 1997; Toledo et al, 2003;Weiss, 1993;Wouters and Vanden Berghe, 2001;van Hoesel and Clark, 1995͒. These algorithms use either single microphone or dual microphones and can be adaptive or nonadaptive in nature.…”

Application of Noise Reduction Algorithm ClearVoice in Cochlear Implant Processing

“…For CI recipients, several studies reported that single-microphone noise reduction techniques improve speech intelligibility in background noise with limited temporal fluctuations (Hochberg et al 1992;Toledo et al 2003;Yang & Fu 2005;Kasturi & Loizou 2007;Buechner et al 2010;Dawson et al 2011;Mauger et al 2012). The reported improvements are modest to small.…”