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市場調查報告書

數位語音助手:平台的商機

Digital Voice Assistants: Platforms Revenues Opportunities 2016-2021

出版商 Juniper Research 商品編碼 369028
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
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數位語音助手:平台的商機 Digital Voice Assistants: Platforms Revenues Opportunities 2016-2021
出版日期: 2016年09月06日 內容資訊: 英文
簡介

本報告提供數位語音助手市場相關調查分析,新興語音介面 (VI) 技術,使用案例,趨勢,經營模式,各產業領域的發展預測等系統性資訊。

第1章 語音助手市場與技術概要

  • 簡介
  • 定義
  • 調查範圍
  • 語音介面 (VI) 技術的要素
  • VI的專利分析

第2章 VI的市場趨勢

  • VI的部門分析
  • VI的部門趨勢
  • VI的價值鏈和商務 模式

第3章 語音助手的預測

  • 簡介
  • 預測手法
  • 摘要的預測
  • 裝機量的預測
  • 收益預測
目錄

Overview

Digital Assistants with voice interactions are becoming a much larger part of how consumers are interacting with devices on a day-to-day basis. We are now seeing the beginnings of a shift in some human-computer interactions, and businesses need to understand what this means and be ready for it.

Our cutting edge research on Digital Voice Assistants provides a clear guide to these emerging voice interface technologies, use cases, trends and business models, as well as providing extensive forecasts for their deployment across a range of different verticals:

  • Mobile OS-based Assistants
  • Mobile App-based Assistants
  • PC OS-based Assistants
  • Automotive Assistants
  • Smart Home Audio Assistants
  • Smart TV-based Assistants
  • Wearable Assistants

Key Features

  • Trend Appraisal : Outline of the current state of Digital Voice Assistant technologies and the trends shaping their development.
  • Business Models : Discussion of the effectiveness and potential for a range of business models for players in the Voice Assistant value chain.
  • Analysis & commentary : on a range of disclosed Voice Assistant patents from a range of companies.
  • Player Assessment : Assesses the offerings of leading players in the Digital Assistant and machine learning space.
  • Benchmark industry forecasts : for size and growth of the various Voice Assistant sectors.

Key Questions

  • 1. Where will digital voice assistants have their biggest success?
  • 2. What new technologies are voice assistants leveraging, and how?
  • 3. What factors will drive up adoption of Voice Assistants, and where will the early successes be?
  • 4. Where can these technologies be monetised to ensure their longevity?
  • 5. What are the new business models that will emerge from this new technology?

Companies Referenced

Amazon, Apple, AYTM, Baidu, BlackBerry, DuckDuckGo, Facebook, Fujitsu, Google, Haptik, Honeywell Partners, IBM, Intel, Intermec IP, ItsMyLab, Jawbone, Microsoft, Nest, Nuance, NVIDIA, Ping An Insurance Group, Robin, Samsung, Sense Labs, Sichuan Changhong Electric Company, Skype, Smart Droid Apps, Smartisan Digital, Sony, SoundHound, Speaktoit, TaskRabbit, Vocollect Healthcare Systems, Viv.ai, West Corporation, Yandex.

Data & Interactive Forecast

The new Digital Voice Assistant forecast suite includes:

  • Market data splits for 8 key regions, and 10 countries including:
    • Brazil
    • Canada
    • China
    • France
    • Germany
    • Japan
    • Mexico
    • South Korea
    • UK
    • US
  • Market data splits for 7 key verticals:
    • Mobile OS-based Assistants
    • Mobile App-based Assistants
    • PC OS-based Assistants
    • Automotive Assistants
    • Smart Home Audio Assistants
    • Smart TV-based Assistants
    • Wearable Assistants
  • Access to the full set of forecast data of 66 tables and over 7,000 data points.

All verticals include:

  • Adoption rates, Assistant installed base and numbers in use. Where appropriate, advertising impressions, ad spend and app revenues are also provided.

Table of Contents

1. Voice Assistant Market & Technologies Introduction

  • 1.1 Introduction
  • 1.2 Definitions
  • 1.3 Research Scope
  • 1.4 Elements of VI (Voice Interface) Technologies
    • Figure 1.1: Juniper Strategy Quadrant for VIs
    • 1.4.1 Microphone Sensors
    • Figure 1.2: Amazon Echo Microphone Array
    • 1.4.2 Speakers
    • 1.4.3 Machine Learning
      • i. Bots & Apps
      • ii. Case Study: Google Tensor Processing Units
      • Figure 1.3: Google TPU Chip
      • iii. Case Study: M by Facebook
  • 1.5 VI Patent Analysis
    • 1.5.1 Amazon
    • Figure 1.4: Vocal User Authentication Process
    • 1.5.2 Apple
    • Figure 1.5: Apple Patent Voice Authentication Process
    • 1.5.3 BlackBerry
    • Figure 1.6: Voice Control Operation Sequence
    • 1.5.4 Fujitsu
    • Figure 1.7: Voice Control Response Process
    • 1.5.5 Google
    • Figure 1.8: Google Probabilistic Modelling System of Voice Inputs & Intended Result
    • Figure 1.9: Automatic Voice Input Monitoring Process
    • Figure 1.10: Interaction Example Using Voice-Monitoring Patent
    • 1.5.6 Honeywell Partners
    • Figure 1.11: Honeywell Partners Speech Sensing & Feedback Process
    • Figure 1.12: Sample Configuration of Honeywell Partners Speech Sensing Building Automation
    • 1.5.7 Intermec IP Corporation
    • Figure 1.13: Intermec Sound Classification Patent Process
    • 1.5.8 Microsoft
    • Figure 1.14: Location-Based Service Query Process
    • Figure 1.15: Multi-User Operating environment for Location-Based Understanding
    • 1.5.9 Ping An Annuity Insurance Company
    • 1.5.10 Sichuan Changhong Electric Company
    • 1.5.11 Smartisan Digital Company
    • Figure 1.16: Category-based Voice Recognition Procedure
    • 1.5.12 Sony
    • Figure 1.17: Sony Gaze Detection & Voice Interface Patent Example
    • 1.5.13 Vocollect Healthcare Systems
    • Figure 1.18: Care Plan Voice Interaction Example
    • 1.5.14 West Corporation
    • Figure 1.19: Customer Services Assistant Process Outline
    • Figure 1.20: Customer Services Assistant Process Example
    • 1.5.15 Juniper's View

2. VI Market Dynamics

  • 2.1 VI Sector Analysis
    • Figure 2.1: Juniper Competitive Web for VI
  • 2.2 VI Sector Dynamics
    • Figure 2.2: Juniper VI Sector Dynamics
    • 2.2.1 VI Drivers
      • iii. Case Study: Alexa Voice Service
      • iv. Smartphone Ubiquity
      • 2.2.2 VI Constraints
      • Figure 2.3: Data Requests to Google 2011-2015 from Government Agencies & Users Specified in Those Requests
      • Figure 2.4: Consequences of Increased Flexibility in Spoken Language Dialogue Systems
      • Figure 2.5: MirrorLink Integration Example
      • vii. Case Study: MirrorLink
    • 2.2.3 VI Trends
    • Figure 2.6: Geographic Distribution & Overlap of Cortana, Google Now & Siri, as of August 2016
  • 2.3 VI Value Chain & Business Models
    • Figure 2.7: Voice Assistant Value Chain
    • 2.3.1 Mobile Device VI Business Models
    • Figure 2.8: Capabilities & Monetisation Strategies of Selected Mobile Assistant Apps
    • 2.3.2 Dedicated Device Voice Assistant Business Models
    • 2.3.3 Device-Agnostic Business Models
    • 2.3.4 Current Player Landscape & Capabilities
    • Figure 2.9: Digital Assistant Player Capabilities

3. Voice Assistant Forecasts

  • 3.1 Introduction
  • 3.2 Forecast Methodology
    • 3.2.1 Forecast Steps
    • Figure 3.1: Smart Mobile Device OS-Based Voice Assistant Forecast Methodology
    • Figure 3.2: Smart Mobile Device App-Based Voice Assistant Forecast Methodology
    • Figure 3.3: PC OS-based Voice Assistant Forecast Methodology
    • Figure 3.4: Smart TV-based Voice Assistant Forecast Methodology
    • Figure 3.5: Automotive Digital Assistants Forecast Methodology
    • Figure 3.6: Smart Home Digital Assistants Forecast Methodology
    • Figure 3.7: Wearables Digital Assistants Forecast Methodology
  • 3.3 Summary Forecasts
    • 3.3.1 Digital Assistant Installed Base Forecasts
    • Figure & Table 3.8: Global Digital Assistants in Use per annum (m) Split by Category 2016-2021
    • 3.3.2 Digital Assistant Revenue Forecasts
      • i. Advertising Spend
      • Figure & Table 3.9: Global Digital Assistant Advertising Spend per annum (m) Split by Category 2016-2021
      • ii. App Revenues
      • Table 3.10: Global Digital Assistant App Revenue per annum (m) Split by Category 2016-2021
  • 3.4 Installed Base Forecasts
    • 3.4.1 Mobile OS-based Digital Assistants
    • Figure & Table 3.11: Global Mobile OS-based Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
    • 3.4.2 PC OS-based Digital Assistants
    • Figure & Table 3.12: Global PC OS-based Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
    • 3.4.3 Mobile App-based Digital Assistants
    • Figure & Table 3.13: Global Mobile App-based Digital Assistants in Use per annum (m) Split by 8 Key Regions 2016-2021
    • 3.4.4 Connected TV-based Digital Assistants
    • Figure & Table 3.14: Global Connected TV-based Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
    • 3.4.5 Automotive Digital Assistants
    • Figure & Table 3.15: Global Automotive Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
    • 3.4.6 Smart Home digital Assistants
    • Figure & Table 3.16: Global Smart Home Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
    • 3.4.7 Wearable-based Digital Assistants
    • Figure & Table 3.17: Global Integrated Wearable Digital Assistants in Use per annum (m) Split by 8 Key Regions, 2016-2021
  • 3.5 Revenue Forecasts
    • 3.5.1 App Revenue Forecasts
      • i. Mobile App Download Revenue
      • Figure & Table 3.18: Global Mobile App Download Revenue per annum ($m) Split by 8 Key Regions, 2016-2021
      • ii. In-app Purchase Revenue
      • Figure & Table 3.19: Global Voice Assistant In-App purchase Revenue per annum ($m) Split by 8 Key Regions 2016-2021
    • 3.5.2 Mobile Advertising Spend
      • i. OS-based Assistant Advertising Spend
      • Figure & Table 3.20: Global Mobile OS-based Voice Assistant Advertising Spend per annum ($m) Spit by 8 Key Regions 2016-2021
      • ii. App-based Assistant Advertising Spend
      • Figure & Table 3.21: Global Mobile App-based Voice Assistant Advertising Spend per annum ($m) Split by 8 Key Regions 2016-2021
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