Deep Learning-Based Ambient Sound and  Language Processing: Cloud to Edge Image

Deep Learning-Based Ambient Sound and Language Processing: Cloud to Edge

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Actionable Benefits

  • Understand the importance of deep learning-based ambient sound and natural language processing in both the cloud and the edge.
  • Learn about key players and enabling technologies.
  • Access internal capabilities and align product development to address the relevant use cases.

Critical Questions Answered

  • Why is edge-based ambient sound and natural language processing gaining momentum in machine learning?
  • What is the current state of maturity for these technologies?
  • What are the use cases that will benefit the most from deep learning-based ambient sound and natural language processing at the edge?            

Research Highlights

  • Comprehensive analysis of current technological and market trends.
  • Profiling of the vendor landscape.
  • Key market activities in edge-based ambient sound and natural language processing.

Who Should Read This?

  • End users that are interested in deep learning-based ambient sound and natural language processing in both the cloud and the edge
  • Innovation leaders looking to understand the potential of edge-based ambient sound and natural language processing
  • Solution providers who are interested in the entire competitive landscape.

Table of Contents

1. EXECUTIVE SUMMARY

2. INTRODUCTION TO NATURAL LANGUAGE PROCESSING

2.1. Speech Processing
2.2. Natural Language Understanding
2.3. Natural Language Generation
2.4. The Focus of Cloud AI Vendors

3. INTRODUCTION TO AMBIENT SOUND PROCESSING

4. MOVING PROCESSING TO THE EDGE

4.1. Edge Natural Language Processing
4.2. Edge Ambient Sound Processing
4.3. Edge AI Chipset

5. KEY PLAYERS

5.1. Edge AI Chipset Vendors
5.2. Edge-Based Software and Turnkey Service Vendors
5.3. Cloud-Based Software and Turnkey Service Vendors

6. MARKET FORECASTS

7. RECOMMENDATIONS