Voice First Tech
- Author Kees Buiel
- Published June 1, 2019
- Word count 661
When you need to solve a problem that involves another person, what’s the best way to solve it? By having a conversation. We’re finally able to communicate with our devices—phones, computers, wearable devices, smart speakers and more—the same way we talk to one another when we need to get things done.
We are approaching a time where we move from typing to speaking to our devices - Voice First. Voice first is here now and being integrated in to all the speaker and voice devices and processes.
As this tech becomes more accepted and user friendly, hiding much of the complexity of voice-enabled technologies, users will use their voice to order groceries, book a cleaner, call a cab (or give commands to a self-driving one), make appointments, remotely control their homes and more and more - I mean we use our voice for loads of things already - it will just be integrated into our tech.
Will this be the 'final' single interface for interacting with a diverse variety of devices at home or on-the-go, making it easier for users to accomplish any task hands-free? I don’t 'think' so, we will have to 'think about that' first.
However voice-first will be a huge step forward and change in the way we connect and control and ask our devices to help us.
Already the comedy has come - check out this - this is just an example of how results will be given for different parts of the world or parts of the country. It’s funny but also has some truth in it!
There are a variety of examples of voice-first tech and use cases; this is a great demonstration of the possibilities today showcased by Alexi team
There is a rising importance of Voice Analytics and Voice-First. Many of us have seen the adverts for switching on security or locking your doors through voice and we maybe seen the movie Her.
However a few of us in the globe are just becoming accustomed to the technology. And as usual many users don’t really understand the tech and can’t use 80% of the features - the point is that even just a few features are convincing user to discover this tech and start using it.
As more people use and develop tools and systems, analytics will help developers better manage expectations, anticipate errors and help users discover features relevant to their needs and drive up adoption of voice-first like Ai Image Processing.
In developing voice tech and text messaging tech there are numerous metrics that can be tracked by developers for voice platform improvement and development. These include:
• Sentiment analysis: The language used, as well as tone or pitch of users, can help to measure the sentiment of a brand or of the user experience itself helping direct support and improve engagement.
• Intent and parameter: Intent (what the user is asking for, like "when is the booking?") and parameter (the specific, contextual request, like "how late are they going to be?") provides insights on consumer behavior.
• Pathing: Pathing includes the steps of the conversation as well as what actions users take afterward.
• Errors: Errors and null statements make apparent where devices and platforms fail their users.
Voice and text applications will become a key function as a part of brand omnichannel strategies - the ability to move with the customer as the customer changes platforms or locations etc.
TonkaBI is the expert in Innovative Data Technology, especially for the Insurance AI Industry! We understand what challenges insurance companies like yours face on a daily basis and we’ll be with you every step of the way, working with you to make this process as effective and as efficient as possible. TonkaBI is a living breathing organism, in all aspects, and if something needs to be adjusted, reorganized or rebuilt, this is something TonkaBI knows how to do this, do it right and do it quickly.
Know more about it at : www.tonkabi.com/artificial-intelligenceArticle source: http://articlebiz.com
There are no posted comments.
- Securely erase your data with Active@ ZDelete
- 30 Largest TensorFlow Datasets for Machine Learning
- Types of Cables and Wires Found in Modern Technology
- SAP S/4 HANA – Empowering Manufacturers Driving Digital Transformation
- Business mistakes contact centres make during cloud migration
- What Is Data Democratization and Why is it Needed?
- Tech Sector to Weather Economic Storm
- 10 Open Datasets for Linear Regression
- Top 10 Stock Market Datasets for Machine Learning
- Best Image Annotation Tools for Computer Vision
- What To Know About iPad Screen Repair
- Robotic process automation (RPA)
- 10 Best Data Annotation Companies for Machine Learning
- 11 Best Named Entity Recognition Tools
- How ADN Helps Crypto Funding Evolve
- The Future of Data Analytics: 5 Predictions for Where We Are Headed
- 10 Data Analytics Terms Every Beginner Should Know
- ADN Coin: Benefits of Holding Our Coin
- Five Benefits of CCTV Cameras That Go Beyond Video Recording
- How to choose your tablet?
- There Is A Lot To Consider When Setting Up A Private Medical Practice
- How Blockchain can Help fight Climate Change and Save the Environment
- Top 20 Twitter Datasets for Natural Language Processing and Machine Learning
- Best Data Labeling Tools for Machine Learning Projects
- What is the Difference Between CNN and RNN?
- Get Machine Learning Training Data Using The Lionbridge Method [A How-To Guide]
- What are Image Annotation Services?
- 10 Best Text Annotation Services and Tools
- Do More with a Creative Photo Editor with Facial Recognition
- An overview of Cloud 3d Print’s objectives