Evaluation of Noise Reduction

Evaluation of Noise Reduction

Evaluation of Digital Noise Reduction Algorithms
Developed at our Hearing Research Center, SpeechTrax underwent a battery of sound quality studies
throughout research and development. Individual parameters of the algorithm were adjusted to
accommodate the listening preferences of patients and to ensure that the algorithm was appropriately
targeting noise in the gaps of speech. These early studies were completed prior to the implementation
of the SpeechTrax in a hearing aid. By focusing early development outside of the hearing aid platform,
appropriate adjustments were easily made. After establishing algorithm parameters that ensured patient
success in a laboratory setting, the next step was clinical validation of SpeechTrax in the
Axio ST hearing aid.
The successful transfer of SpeechTrax to the MicroTech Axio ST hearing aids was validated through
systematic clinical research. Forty-four hearing-impaired adults participated in a comprehensive clinical trial.
Detailed results of this clinical trial are presented and discussed by Pisa, Burk, and Galster (In Press). In
their study, the authors found that the Axio ST hearing aids significantly improved patients’ ability to tolerate
noisy environments. Participants also reported reduced listening effort, as measured by the Device-Oriented
Subjective Outcome Scale (DOSO) (Cox, Alexander & Xu, 2009), with the test devices when compared to
their own hearing aids.
Preservation of Speech in Noise
A system that is designed to reduce noise between gaps in speech must also retain the integrity of the
valuable speech signal. Because speech modulations occur over a period of milliseconds, this can be
a challenging task. If hearing aid output is reduced during gaps in speech, appropriately prescribed gain
must be reapplied to the speech signal when it returns. A poorly designed noise reduction algorithm may
not accurately track speech modulations, thereby compromising the integrity of the speech signal. A major
design focus of SpeechTrax was to ensure the preservation of these speech cues while aggressively
reducing noise.
An electroacoustic benchmarking evaluation developed by Hagerman and Olofsson (2004) was
used to illustrate the speech-preserving capability of SpeechTrax. This evaluation method allows for
the extraction of speech from a background of noise after processing through a digital noise reduction
algorithm. For the purpose of this paper, the extracted waveforms are used to provide a qualitative visual
example of how digital noise reduction algorithms implemented in today’s hearing aids may distort or
reduce speech when presented in background noise.
The test method developed by Hagerman and Olofsson (2004) is described in an excerpt from their
publication: Our approach is to present speech and noise simultaneously and make two measurements,
one of them with the noise phase reversed. Taking the sum of the corresponding two output signals, or the
difference, the output speech or the output noise can be extracted. Thus, the gain can be calculated for
each of them, although they are present at the same time and influence the signal processing of the
hearing aid in a normal way. (p. 356)

Author: fmpmedia

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