Search

Cochlear implants allow most patients with profound deafness to successfully communicate under optimal listening conditions. However, the amplitude modulation (AM) information provided by most implants is not sufficient for speech recognition in realistic settings where noise is typically present. This study added slowly varying frequency modulation (FM) to the existing algorithm of an implant simulation and used competing sentences to evaluate FM contributions to speech recognition in noise. Potential FM advantage was evaluated as a function of the number of spectral bands, FM depth, FM rate, and FM band distribution. Barring floor and ceiling effects, significant improvement was observed for all bands from 1 to 32 with the additional FM cue both in quiet and noise. Performance also improved with greater FM depth and rate, which might reflect resolved sidebands under the FM condition. Having FM present in low-frequency bands was more beneficial than in high-frequency bands, and only half of the bands required the presence of FM, regardless of position, to achieve performance similar to when all bands had the FM cue. These results provide insight into the relative contributions of AM and FM to speech communication and the potential advantage of incorporating FM for cochlear implant signal processing.

Speech recognition performance was measured in normal-hearing and cochlear-implant listeners with maskers consisting of either steady-state speech-spectrum-shaped noise or a competing sentence. Target sentences from a male talker were presented in the presence of one of three competing talkers (same male, different male, or female) or speech-spectrum-shaped noise generated from this talker at several target-to-masker ratios. For the normal-hearing listeners, target-masker combinations were processed through a noise-excited vocoder designed to simulate a cochlear implant. With unprocessed stimuli, a normal-hearing control group maintained high levels of intelligibility down to target-to-masker ratios as low as 0 dB and showed a release from masking, producing better performance with single-talker maskers than with steady-state noise. In contrast, no masking release was observed in either implant or normal-hearing subjects listening through an implant simulation. The performance of the simulation and implant groups did not improve when the single-talker masker was a different talker compared to the same talker as the target speech, as was found in the normal-hearing control. These results are interpreted as evidence for a significant role of informational masking and modulation interference in cochlear implant speech recognition with fluctuating maskers. This informational masking may originate from increased target-masker similarity when spectral resolution is reduced.

Amplitude modulation (AM) and frequency modulation (FM) are commonly used in communication, but their relative contributions to speech recognition have not been fully explored. To bridge this gap, we derived slowly varying AM and FM from speech sounds and conducted listening tests using stimuli with different modulations in normal-hearing and cochlear-implant subjects. We found that although AM from a limited number of spectral bands may be sufficient for speech recognition in quiet, FM significantly enhances speech recognition in noise, as well as speaker and tone recognition. Additional speech reception threshold measures revealed that FM is particularly critical for speech recognition with a competing voice and is independent of spectral resolution and similarity. These results suggest that AM and FM provide independent yet complementary contributions to support robust speech recognition under realistic listening situations. Encoding FM may improve auditory scene analysis, cochlear-implant, and audio- coding performance. [ABSTRACT FROM AUTHOR]

Different from traditional Fourier analysis, a signal can be decomposed into amplitude and frequency modulation components. The speech processing strategy in most modem cochlear implants only extracts and encodes amplitude modulation in a limited number of frequency bands. While amplitude modulation encoding has allowed cochlear implant users to achieve good speech recognition in quiet, their performance in noise is severely compromised. Here, we propose a novel speech processing strategy that encodes both amplitude and frequency modulations in order to improve cochlear implant performance in noise. By removing the center frequency from the subband signals and additionally limiting the frequency modulation's range and rate, the present strategy transforms the fast-varying temporal fine structure into a slowly varying frequency modulation signal. As a first step, we evaluated the potential contribution of additional frequency modulation to speech recognition in noise via acoustic simulations of the cochlear implant. We found that while amplitude modulation from a limited number of spectral bands is sufficient to support speech recognition in quiet, frequency modulation is needed to support speech recognition in noise. In particular improvement by as much as 71 percentage points was observed for sentence recognition in the presence of a competing voice. The present result strongly suggests that frequency modulation be extracted and encoded to improve cochlear implant performance in realistic listening situations. We have proposed several implementation methods to stimulate further investigation. [ABSTRACT FROM AUTHOR]