Pitch Perception With the Temporal Limits Encoder for Cochlear Implants

Abstract

The temporal-limits-encoder (TLE) strategy has been proposed to enhance the representation of temporal fine structure (TFS) in cochlear implants (CIs), which is vital for many aspects of sound perception but is typically discarded by most modern CI strategies. TLE works by computing an envelope modulator that is within the temporal pitch limits of CI electric hearing. This paper examines the TFS information encoded by TLE and evaluates the salience and usefulness of this information in CI users. Two experiments were conducted to compare pitch perception performance of TLE versus the widely-used Advanced Combinational Encoder (ACE) strategy. Experiment 1 investigated whether TLE processing improved pitch discrimination compared to ACE. Experiment 2 parametrically examined the effect of changing the lower frequency limit of the TLE modulator on pitch ranking. In both experiments, F0 difference limens were measured with synthetic harmonic complex tones using an adaptive procedure. Signal analysis of the outputs of TLE and ACE strategies showed that TLE introduces important temporal pitch cues that are not available with ACE. Results showed an improvement in pitch discrimination with TLE when the acoustic input had a lower F0 frequency. No significant effect of lower frequency limit was observed for pitch ranking, though a lower limit did tend to provide better outcomes. These results suggest that the envelope modulation introduced by TLE can improve pitch perception for CI listeners.

Comparable Encoding, Comparable Perceptual Pattern: Acoustic and Electric Hearing

“…Instead, temporal envelopes from fixed bands are extracted where phonetic cues are found to be implicitly represented. For example, F0 can be found in the periodicity on the envelope [12] and formants can be estimated by comparing the relative power of all bands [13]. More recent strategies have inherited key features of CIS, and the approach is still an option for almost all modern CI products.…”

Review of techniques used in speech signal processing

“…By incorporating prosodic information, TTS systems can imbue synthesized speech with appropriate emotional and linguistic cues, elevating the overall quality and human-like nature of the output [7]. In conjunction with RNNs, CNNs, and prosody modeling, a spectrum of complementary techniques further enhances the capabilities of spoken language processing [8]. Speaker diarization, for instance, aids in distinguishing between different speakers in a conversation, enabling systems to transcribe and attribute speech to specific individuals-an essential function in tasks like transcription services and meeting recordings [8].…”

“…In conjunction with RNNs, CNNs, and prosody modeling, a spectrum of complementary techniques further enhances the capabilities of spoken language processing [8]. Speaker diarization, for instance, aids in distinguishing between different speakers in a conversation, enabling systems to transcribe and attribute speech to specific individuals-an essential function in tasks like transcription services and meeting recordings [8]. Voice Activity Detection (VAD) serves as a crucial preprocessing step in speech processing by identifying segments of audio containing actual speech and filtering out silence or non-speech regions [9].…”

Cochlear-implant Mandarin tone recognition with a disyllabic word corpus

“…This is perhaps unsurprising given CI recipients' weaker and more variable abilities to extract pitch cues from acoustic signals (Tao et al, 2015 ; Mok et al, 2017 ; Vandali et al, 2017 ). Limitations in pitch extraction can occur on multiple stages of the CI supplied auditory system, from the device's signal processing strategy through peripheral auditory neural processing, all the way to auditory cortical processing and cognition (Zhang, 2019 ; Zhou et al, 2022 ).…”