Speech Recognition Software 2017 Global Market Expected to Grow at CAGR 16.99% and Forecast to 2020

WiseGuyReports.Com Publish a New Market Research Report On - “Speech Recognition Software 2017 Global Market Expected to Grow at CAGR 16.99% and Forecast to 2020”.

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New York, NY -- (SBWire) -- 08/11/2017 --The analysts forecast the global speech recognition software market to grow at a CAGR of 16.99% during the period 2016-2020.

A speech recognition software identifies words spoken by an individual or speaker into a microphone, converts them into a computer-readable format, and responds automatically. These software applications recognize speech in multiple languages. These applications are used both by individual consumers and enterprises in the healthcare; banking, financial services, and insurance; legal; and telecommunications sectors for a number of purposes including fraud management, speaker verification, speaker identification, biometrics, and vehicle telematics. The biometrics segment is seeing a high demand for speech recognition software because of the growing instances of fraud. Vendors are developing easy-to-deploy and cost-effective speech recognition applications that help in fraud management.

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Covered in this report

The report covers the present scenario and the growth prospects of the global speech recognition software market for 2016-2020. To calculate the market size, the report considers the revenue generated from the sales of speech recognition solutions, including software, integrated solutions, and services.

The market is divided into the following segments based on geography:
- Americas
- APAC
- EMEA

The report, Global Speech Recognition Software Market 2016-2020, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the key vendors operating in this market.

Key vendors
- AT&T
- IBM
- Microsoft
- Nuance Communications

Other prominent vendors
- Dolby Systems
- LumenVox
- OnMobile Global
- Raytheon BBN Technologies
- Sensory
- Tellme Networks
- Voxeo

Market driver
- Increased use of biometrics
- For a full, detailed list, view our report

Market challenge
- Lack of accuracy
- For a full, detailed list, view our report

Market trend
- Increased use of voice passwords
- For a full, detailed list, view our report

Key questions answered in this report
- What will the market size be in 2020 and what will the growth rate be?
- What are the key market trends?
- What is driving this market?
- What are the challenges to market growth?
- Who are the key vendors in this market space?
- What are the market opportunities and threats faced by the key vendors?
- What are the strengths and weaknesses of the key vendors?

Report Details @ https://www.wiseguyreports.com/reports/390257-global-speech-recognition-software-market2016-2020

Table Of Contents – Major Key Points

PART 01: Executive summary
- Highlights

PART 02: Scope of the report
- Market overview
- Top-vendor offerings

PART 03: Market research methodology
- Research methodology
- Economic indicators

PART 04: Introduction
- Key market highlights

PART 05: Market landscape
- Market overview
- Technology segments
- Advantages and disadvantages of speech recognition software
- Market size and forecast
- Global speech recognition market by product segmentation 2015

PART 06: Five forces analysis

PART 07: Market segmentation by application
- Global speech recognition software market by application

PART 08: Market segmentation by end-user
- Enterprise users
- Individual users

PART 09: Geographical segmentation
- Global speech recognition software market by region
- Global speech recognition software market by region 2015-2020 (revenue)

PART 10: Key leading countries
- US
- UK
- Japan

PART 11: Buying Criteria

PART 12: Market drivers
- Increased use of biometrics
- Demand for speech recognition on mobile devices
- Use of speech recognition in healthcare industry
- Need to improve competitive approach

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