Introduction

The integration of artificial intelligence into hearing aids represents one of the most significant technological advances in audiology since digital signal processing. As the audiologists at Liverpool Hearing Centre observe daily, these AI-powered devices fundamentally transform how patients experience sound in challenging listening environments. This comprehensive analysis examines how ReSound Vivia's AI technology compares to leading competitors, helping you understand which system might best serve your hearing needs.

Understanding AI in Hearing Aids

The AI Revolution in Audiology

Traditional hearing aids processed sound using predetermined algorithms. However, modern AI systems learn from millions of real-world sound examples to make instantaneous decisions about which sounds to amplify or suppress. This process represents a paradigm shift comparable to moving from film photography to digital imaging.

Key AI Advantages:

• Real-time sound classification
• Adaptive noise reduction
• Context-aware speech enhancement
• Automatic environment detection
• Personalised listening preferences

Deep Neural Networks Explained

Deep Neural Networks (DNNs) are sophisticated AI systems inspired by how the human brain processes information. In hearing aids, DNNs analyse incoming sounds through multiple layers of processing, each extracting increasingly complex acoustic features. This multi-layered approach allows the hearing aid to:

1. Identify speech patterns from various speakers
2. Distinguish speech from complex background noise
3. Adapt to individual voice characteristics
4. Maintain spatial awareness while focusing on speech

ReSound Vivia's AI Technology

Dual-Chip Architecture Detail

ReSound's approach combines two specialised processors:

360 Chip: Handles traditional hearing aid functions including:

• Basic amplification
• Feedback management
• Compression algorithms
• Bluetooth connectivity

DNN Chip: Dedicated entirely to AI processing:

• Real-time speech enhancement
• Environmental classification
• Noise reduction algorithms
• Adaptive sound processing

This separation allows each chip to be optimised for its specific functions, potentially delivering superior performance compared to systems attempting to integrate all functions on a single processor.

Intelligence Augmented AI Processing

ReSound's system processes acoustic information using several sophisticated algorithms:

1. Intelligent Noise Tracker: Continuously monitors and adapts to changing noise environments
2. Speech Focus: Prioritises speech based on head orientation
3. Real-time Sound Classification: Instantly identifies and responds to different acoustic scenarios
4. Binaural Processing: Coordinates information between both ears for optimal spatial awareness

Training and Development

ReSound trained their DNN on 13.5 million sentences across multiple languages, accents, and acoustic conditions. This extensive training dataset includes:

• Male and female voices
• Children's speech patterns
• Accented speech
• Whispered conversations
• Noisy restaurant environments
• Traffic and urban soundscapes

Competitor AI Technologies

Phonak Infinio Sphere

Architecture: Phonak employs a dual-chip system called Phonak SmartSpeech Technology 2.0:

• Era chip: Manages traditional hearing aid functions
• DEEPSONIC chip: Dedicated AI processor

Key Features:

• Real-time speech enhancement in 360 degrees
• Claims to provide 53 times more operations than previous generation
• Focuses on preserving naturalness whilst enhancing speech
• Spheric Speech Clarity for omnidirectional performance

Clinical Results: Studies suggest a 16% improvement in speech understanding in noise compared to previous Phonak models.

Signia IX

Architecture: Unique dual-processor approach:

• Speech processor: Dedicated to enhancing and preserving speech characteristics
• Noise processor: Focused exclusively on identifying and reducing unwanted sounds

Key Features:

• RealTime Conversation Enhancement
• Dynamic Soundscape Processing
• Spatial Speech Focus
• Own Voice Processing (OVP 2.0)

Clinical Performance: Clinical trials demonstrate 35% reduction in listening effort in noisy environments.

Starkey Edge AI

Architecture: Single-chip design with integrated AI processing

Key Features:

• Industry-leading edge computing
• Neuro Sound Technology
• Edge Mode for automatic sound analysis
• Healthable platform for cognitive tracking

Unique Approach: Integrates health monitoring capabilities alongside hearing enhancement, including:

• Fall detection
• Physical activity tracking
• Brain health monitoring through listening effort measurement

Oticon Intent

Architecture: Polaris R chip with integrated AI capabilities

Key Features:

• Deep Neural Network v2.0
• MoreSound Intelligence 3.0
• Real-world trained AI
• 4D sensor integration for movement and conversation analysis

Clinical Evidence: Studies show 45% improvement in speech understanding in noise compared to traditional directional microphones.

Detailed Performance Comparison

Speech-in-Noise Performance

SNR = Signal-to-Noise Ratio (lower numbers indicate better performance)

Real-World Performance Analysis

Restaurant Environment:

• Phonak Infinio Sphere: Excels in 360-degree speech enhancement
• ReSound Vivia: Superior spatial awareness maintenance
• Signia IX: Effective at reducing competing conversations
• Oticon Intent: Strong performance with multiple talkers
• Starkey Edge AI: Good but slightly behind others in extreme noise

Lecture Halls/Group Settings:

• ReSound Vivia: Excellent automatic focusing on primary speaker
• Oticon Intent: Outstanding with 4D sensor integration
• Phonak Infinio Sphere: Strong omnidirectional performance
• Signia IX: Good speech clarity but may reduce naturalness
• Starkey Edge AI: Reliable but requires more manual adjustment

Technical Implementation Differences

Chip Architecture Implications

Dual-Chip Advantages:

• Dedicated processing power for AI functions
• Potentially superior performance in specific tasks
• Better heat management
• More upgrade flexibility

Single-Chip Advantages:

• Lower power consumption
• Smaller form factors possible
• Potentially more seamless integration
• Reduced manufacturing complexity

Processing Speed and Latency

• ReSound Vivia: Processes 4.9 trillion operations per day with minimal latency
• Phonak Infinio Sphere: Claims fastest processing with virtually no delay
• Signia IX: Optimised for real-time performance with separate processors
• Starkey Edge AI: Edge computing ensures rapid response times
• Oticon Intent: Polaris R chip provides efficient processing with low power consumption

Clinical Considerations for Audiologists

Fitting Requirements

ReSound Vivia:

• Requires Real Ear Measurements for optimal performance
• AI features fully integrated, minimal manual adjustment needed
• Professional programming essential for best results

Phonak Infinio Sphere:

• Automatic fitting possible but professional verification recommended
• DEEPSONIC chip may require specific programming approaches
• Good initial fit often achieved with standard protocols

Signia IX:

• Benefits from detailed sound preference profiling
• May require fine-tuning of speech/noise processor balance
• Own Voice Processing needs careful calibration

Patient Suitability

Best Candidates for Each System:

ReSound Vivia:

• Patients prioritising spatial awareness
• Users wanting advanced app control
• Those with variable listening environments

Phonak Infinio Sphere:

• Patients struggling in group conversations
• Users in consistently challenging noise
• Those wanting automatic solutions

Signia IX:

• Patients sensitive to own voice
• Users in predictable environments
• Those wanting natural sound quality

Starkey Edge AI:

• Health-conscious patients
• Users wanting cognitive monitoring
• Those in moderate noise environments

Oticon Intent:

• Patients with complex listening needs
• Users prioritising brain health
• Those in dynamic environments

Future of AI in Hearing Aids

Emerging Technologies

1. Machine Learning Evolution: Continuous learning from user preferences
2. Cloud-Based Processing: Offloading complex calculations to remote servers
3. Biometric Integration: Heart rate and stress level considerations
4. Real-Time Language Translation: Breaking down language barriers
5. Predictive Adjustments: Anticipating environment changes

Research and Development

Current research focuses on:

• Reducing processing latency to under 1ms
• Implementing true unsupervised learning
• Developing situation-specific AI models
• Creating personalised acoustic filters
• Integrating with smart home ecosystems

Liverpool Hearing Centre's Expert Perspective

Clinical Experience

Our audiologists have observed distinct patterns in patient satisfaction with different AI systems:

ReSound Vivia:

• Patients appreciate maintained spatial awareness
• Excellent for users prioritising natural sound
• Strong performance in outdoor environments

Phonak Infinio Sphere:

• Particularly successful for restaurant dining
• Good for patients with severe speech-in-noise difficulties
• Quick adaptation period for most users

Signia IX:

• Excellent for patients bothered by own voice amplification
• Good for users in consistent acoustic environments
• Requires patient involvement in fine-tuning

Fitting Outcomes

Based on our clinical data:

• 85% of patients show measurable improvement with any AI system
• Dual-chip systems show 15% better performance in extreme noise
• Patient preference varies significantly based on listening priorities
• Professional fitting crucial regardless of AI system chosen

Choosing the Right AI Hearing Aid

Decision Framework

When selecting an AI hearing aid, consider:

1. Primary Listening Challenges:

   • Group conversations → Phonak Infinio Sphere
   • Variable environments → ReSound Vivia
   • Own voice issues → Signia IX
   • Health monitoring → Starkey Edge AI
   • Complex soundscapes → Oticon Intent

2. Technical Preferences:

   • Maximum processing power → Dual-chip systems
   • Best battery life → Single-chip systems
   • Latest connectivity → Bluetooth LE Audio systems
   • Smartphone integration → All offer excellent app support

3. Professional Support Needs:

   • All AI systems require professional fitting
   • Some benefit more from fine-tuning than others
   • Liverpool Hearing Centre provides comprehensive support for all systems

Conclusion

The landscape of AI hearing aids is remarkably diverse, with each system offering unique advantages. ReSound Vivia's dual-chip architecture provides powerful AI processing while maintaining excellent spatial awareness, making it ideal for users who prioritise natural sound quality with enhanced speech clarity. However, the best choice depends on individual hearing needs, lifestyle requirements, and personal preferences.

At Liverpool Hearing Centre, our expert audiologists help patients navigate these complex decisions through comprehensive assessments, detailed consultations, and trial periods. The future of AI in hearing aids is bright, with continuous improvements promising even better outcomes for those with hearing loss.

References

1. Better Hearing Institute. (2024). Artificial Intelligence in Hearing Aids: Clinical Effectiveness Study.
2. American Academy of Audiology. (2024). Comparative Analysis of AI Processing in Modern Hearing Aids.
3. ReSound. (2025). Vivia DNN Technology: Technical Specifications and Clinical Data.
4. Phonak. (2025). DEEPSONIC Chip Performance Analysis in Real-World Conditions.
5. Signia. (2024). Dual-Processor Architecture: Speech and Noise Separation Technology.
6. Starkey. (2024). Edge Computing in Hearing Aids: Performance and Power Efficiency.
7. Oticon. (2024). Polaris R Chip: Integrated AI Processing Capabilities.
8. European Telecommunications Standards Institute. (2024). Bluetooth LE Audio Standards for Hearing Aids.