Skip to content

Understanding AI hearing aids

Learn how Artificial Intelligence (AI) and Deep Neural Networks (DNN) improve real world listening through clearer speech, listening effort and increased environmental awareness.

Shop AI hearing aids

Our human
approach to AI

Rooted in our Organic Hearing™ philosophy, we apply AI within our hearing solutions to support the brain’s natural way of functioning – making hearing sound and feel natural, empowering the user to stay in control, and enhancing everyday communication without taking over.

“Our approach sets ReSound AI hearing aids apart and provides the greatest benefit to the end user. AI is applied in such a way that we spotlight the important speech that is front and center, rather than the most predominant speech that the AI might select. This approach to AI never gets in the way of life's most important moments, but rather makes sure they are heard.”


Laurel Christensen, Ph.D., Chief Audiology Officer, GN Hearing

Award-winning
AI hearing aids 

ReSound is proudly at the forefront of AI hearing technology, recognized by the industry for our use of AI in hearing aids, which are designed to empower hearing aid users. 

AI in hearing technology

AI hearing aids combine fast rule-based processing (volume, feedback control, directionality) with adaptive machine learning models, such as DNNs. Watch this short video to see how AI hearing aids work.

Why AI hearing technology matters 

AI allows the hearing aids to automatically classify and adapt to different listening environments. In noise management features, AI helps to separate speech from background noise, improving clarity and reducing listening effort.

“Importantly, we focus on user-centric design in AI that results in augmented intelligence. In wave 1, we used AI to significantly reduce the time it would have taken to develop our technology, to support our engineers with their research and development; and in wave 2, to partner people with hearing loss by incorporating AI into our hearing solutions.”


Andrew Dittberner, Chief Scientific Officer, GN Advanced Science

10 ways AI hearing aids help in everyday situations

1.
Automatically Focus on Key Conversations

AI hearing aids can help patients focus on the primary speaker in complex sound environments. By reducing competing background noise in cafés, offices, or family gatherings, they support better speech understanding and more effortless communication, which can increase satisfaction with real‑world performance.

2.
Improve Outcomes in Group Dining Situations

Restaurants and family dinners are a common pain point for people with hearing loss. AI can help the hearing aids prioritize speech from the table and reduce clutter from surrounding conversations and dishes. This supports more successful social participation, a key factor in perceived benefit and long‑term loyalty.

3.
Support Comfort in Challenging Public Spaces

In buses, trains, and shopping centres, AI continuously analyses the sound scene and adapts in real time. Sudden loud sounds can be softened, while important cues like nearby voices and announcements remain clear. This can help reduce listening stress and support daily comfort, especially for sound‑sensitive users.

4.
Enhance Speech Access In Meetings

In offices and meeting rooms, AI can help separate speech from room noise, ventilation, or keyboard sounds. This makes it easier for patients to follow colleagues and presenters, even when they turn away or speak softly. Strong performance at work is often a critical driver of perceived value and device acceptance.

5.
Optimise TV And Streaming Experiences

When patients watch TV or stream content, AI can help optimise sound for speech clarity while preserving a natural overall sound. This may reduce the need to increase the TV volume for others and can improve shared listening experiences at home, which often influences family support for hearing care.

6.
Support Natural Communication at Home

AI can help hearing aids adapt to a patient’s typical home environment over time. Whether they are cooking in a noisy kitchen or talking in the living room, the system supports clearer, more natural conversations with family members. Less need for manual adjustments often translates into higher day‑to‑day satisfaction.

7.
Balance Awareness and Focus Outdoors

Outdoors, AI can help users stay aware of important environmental sounds, such as bikes, cars, or someone calling their name, while still supporting clear conversations. This balance between focus and awareness supports safety, confidence, and participation in everyday activities like walking, shopping, or commuting.

8.
Enable Clearer Calls Across Listening Environments

For phone and video calls, AI‑enhanced processing can support clearer speech in both quiet and noisy situations. Whether patients are at home, in the office, or in transit, this can help them stay connected with family, friends, and colleagues, addressing a frequent real‑world complaint in follow‑up appointments.

9.
Help Reduce Listening Effort Over the Day

Listening with hearing loss is demanding, especially in changing environments. AI systems work continuously in the background, adjusting as sound scenes change. This can reduce the effort needed to follow conversations, supporting less fatigue and better adherence to all‑day hearing aid use.

10.
Personalise Sound to Individual Routines

Over time, AI can help tailor sound processing more closely to a patient’s preferences in typical listening situations. This supports a more personalised, predictable hearing experience at work, at home, and socially. For clinics, this can mean fewer fine‑tuning visits and a stronger perceived fit to each user’s lifestyle.

How we use AI in hearing aids Shop AI hearing aids

1. Assess

Microphones pick up the entire sound scene. Feedback management auto-detects and reduces whistling.

2. Decide

Algorithms and DNNs identify speech vs. background noise.
Environmental classification picks the best strategy for the scene.

3. Act

Beamforming and denoising are applied so speech is clearer, while important environmental sounds remain audible.
The noise management strategy of DNN denoising enhances speech.

DNN in AI hearing aids

Deep neural networks are amazing. Click on the boxes below to unfold further facts and details about how we use DNN in our AI hearing aids to separate speech from complex noise – the core challenge for hearing aid users.

How DNNs are inspired by the brain

Learn more

How our DNN stands out

Learn more

Leading combination of key features

Learn more

3 things to remember when explaining DNN

Learn more

Get AI training

Let us guide you through our latest AI hearing aid technology and features, and get tips on how to explain and recommend the benefits of AI hearing aids to your patients.

“ReSound values our partnerships with hearing care professionals and strives to provide the best solutions for your patients just as you do. Our approach to AI puts the patient at the center. At ReSound, we look at AI as a tool to help listeners both hear what they want to hear and hear it comfortably.”


Laurel Christensen, Ph.D., Chief Audiology Officer, GN Hearing

Common questions about AI hearing aids

Our approach to AI is that we seek to empower the hearing care professional and the hearing aid user and not replace them. This continues to be our drive when we innovate with AI and is core to our beliefs.

No, our hearing solutions do not record anything that the hearing aid user hears or says.

All features within hearing solutions will cause battery drain. DNN-powered features are particularly 'power hungry,' however we have designed our AI features to ensure that the end user is guaranteed a full day of battery life with our rechargeable solutions. This includes the use of the DNN denoising feature. In fact, we have the most efficient DNN, which is 17x more efficient that our closest competitor.4

Our solutions store the hearing aids’ behavior over time but do not learn from end-user preferences. This information can be accessed by hearing care professionals via the data logging function in the fitting software and can be enabled or disabled at any time. The hearing aids will not automatically adjust based on end-user preferences. We believe in end-user empowerment; therefore they have the option to adjust their own solutions and even to store favorite settings in our app.

No, we take privacy seriously and ensure we adhere to all required governances and regulations, both country-specific and globally. For more information, contact us.

When considering AI and the hearing aid features, all processing occurs within the device. For example, the DNN has its own dedicated chip and the DNN itself is trained within a laboratory. DNNs can be very 'power hungry,' however we have designed ours to be the most efficient in the industry, guaranteeing a full day of battery.

Our environmental classification system has been designed to classify in 7 different real-world situations, from soft speech to speech in loud noise. This classification strategy ensures 91% accuracy in correctly identifying the most challenging of sound environments and is therefore the most accurate environmental classifier in the industry.5

From internal studies, we established that there was an 89% preference for our latest speech-in-noise feature compared to legacy,6 but also a 5.7dB mean benefit improvement for speech in noise compared to our closest competitor.7

Not only have we validated the performance of our solutions internally, but we also recently had external validations completed by the University of Oldenburg.

They concluded that our solutions are top-rated for speech intelligibility in noise, demonstrating a strong performance compared to other market-leading hearing aids in group conversations and selective attention tasks.8 We were also validated as being the best for speech intelligibility in noise than any other DNN denoising solution, as it was proven to be significantly better in group conversations and selective attention performance.8

 

  1. Jespersen, Dieu & Rubachandran (2025)
  2. GN Proprietary data on file (2025)
  3. Validated by Oldenburg University compared to other market-leading DNN denoising hearing aids. Quilter, Heeren & Jespersen (2026)
  4. Jespersen, Dieu & Rubachandran (2025)
  5. Groth & Cui (2024)
  6. Jespersen (2024)
  7. GN Proprietary data on file (2025)
  8. Quilter, Heeren & Jespersen (2026)

Shop now