After the two streams have been processed independently, they are mixed intelligently based on a soundscape analysis to form the final output.įigure 1. The target sound may be provided more linear gain and less gain reduction by the DNR to further enhance its salience, while background noise may be processed with more compression and more gain reduction. Each stream is analyzed and processed using independent compression and noise reduction parameters. This can be achieved by using bilateral dual microphones to create two different polar patterns for the front and the back sources.
One stream consists of sounds originating from the front, while the other stream contains sounds coming from the back. Specifically, the input signal is split into two separate signal streams (Figure 1). Signia recently introduced split processing, called Augmented Focus, in its Augmented Xperience (AX) platform to separately process sounds arriving from different directions to enhance the contrast between speech and background noise (Best et al., 2021). This limits the improvement of the SNR at the hearing aid output. Consequently, the same DNR and compression settings will be applied to both the speech and noise present in the post-microphone signal.
In a traditional hearing aid, the input signal, including speech and background noise, is first processed by the microphone system before it is processed by the compressor and various noise reduction algorithms. The polar pattern of the microphone can vary adaptively depending on the nature, intensity, and azimuth of speech and noise. In the optimal listening condition, when the talker(s) of interest is spatially separated from noise, adaptive directional microphones reduce the overall output level while improving the output signal-to-noise ratio. The effectiveness of directional microphones, including adaptive directional microphones (ADIRs), is predicated on the spatial separation of speech from other extraneous noises. Definitions of common signal processing terms.ĭirectional technology also has limitations. Output SNR: Ratio of speech and noise levels measured at the hearing aid output after hearing aid processing. Output level: Sound pressure level measured at the hearing aid output after hearing aid processing. Input SNR: Ratio of speech and noise levels measured at the listener position without hearing aid processing. Input level: Sound pressure level measured at the listener position without hearing aid processing. Table 1 includes definitions of signal processing terms as they are used here. When and how much gain reduction occurs in a DNR algorithm is affected by the input level, the estimated input SNR, and the modulation characteristics of the input signal. In contrast, when speech and noise occupy the same frequencies, the overall output level in each channel is reduced, but the overall signal-to-noise ratio (SNR) within that same channel may not be improved. For example, steady-state noise from a household appliance such as a refrigerator or air conditioner is spectrally distinct from the human voice thus DNR algorithms can be quite effective at reducing this type of diffuse background noise with little impact on gain for speech. If speech and noise are spectrally distinct, a decrease in overall output level and an overall SNR improvement may be realized. This difference allows the DNR algorithms to reduce gain in channels dominated by noise while retaining gain in the channels dominated by speech. It is well-known that directional technology improves speech recognition performance in noise compared to omnidirectional microphones, while DNR algorithms typically improve listening comfort and noise tolerance with limited improvement in speech intelligibility noted in some studies (see Ricketts et al., 2019 for a review).Īn assumption used by many modulation-based DNR algorithms is that speech and noise signals occupy different spectral regions and that they have different modulation characteristics. Hearing aid technologies, for decades, have relied on adaptive directional microphones (ADIR) and digital noise reduction (DNR) algorithms to improve speech understanding and/or listening comfort for wearers.