What voice platforms are best for developing voice assistants?

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Voice assistants are becoming more popular and powerful, enabling users to interact with devices and services through natural language. But how do you develop a voice assistant that can understand and respond to different commands, intents, and contexts? In this article, you will learn about some of the best voice platforms that can help you create and deploy voice assistants for various scenarios and domains.

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Eduardo Luis Arana

IT MSE Product Manager – Customer AI | Solution Architect GenAI | Generative AI Expert | Digital Transformation |…

1 What are voice platforms?

Voice platforms are software tools and frameworks that provide the necessary components and capabilities for developing voice assistants. They typically include features such as speech recognition, natural language understanding, dialog management, text-to-speech, and voice user interface design. Some voice platforms also offer integrations with other services and platforms, such as cloud computing, analytics, databases, and webhooks.

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Eduardo Luis Arana

IT MSE Product Manager – Customer AI | Solution Architect GenAI | Generative AI Expert | Digital Transformation | Automation Freak @ Nestlé :)
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OpenAI whisper works pretty well for speech to text functions. There are others like Google speech to text that works also for some small projects. But I've tested whisper and the results, for English based projects are great.

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Giovanni Toschi

Sr. Director, Artificial Intelligence + Deploying AI agents at scale = Your Guide on the Journey to Automation
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Voice platforms are systems that enable the development of voice assistants, like Amazon Alexa or Google Assistant. They use speech recognition and natural language understanding to interpret voice commands and perform tasks. These platforms provide the necessary tools for developers to create voice-enabled applications, catering to a range of functionalities and user interactions. They're chosen based on target audience, device compatibility, and desired features, offering a hands-free, intuitive user experience.

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2 Why use voice platforms?

Voice platforms can simplify and accelerate the development process of voice assistants by providing ready-made solutions and best practices. They can also reduce the cost and complexity of maintaining and scaling voice assistants by handling the infrastructure and security aspects. Voice platforms can also enable you to leverage existing data and resources, such as intents, entities, dialogs, and voice models, to create more robust and versatile voice assistants.

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Giovanni Toschi

Sr. Director, Artificial Intelligence + Deploying AI agents at scale = Your Guide on the Journey to Automation
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Adopting voice platforms offers strategic advantages like enhanced user engagement and accessibility. They cater to a wide audience, including those with disabilities, and facilitate multitasking. This leads to improved user satisfaction and loyalty. For businesses, voice technology is a tool for innovation, setting them apart from competitors. It also streamlines operations and enhances customer service efficiency. Leveraging voice platforms can provide valuable customer insights and give businesses a competitive edge in the digital marketplace.

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3 What are some of the best voice platforms?

The voice platform market is full of options, each with its own unique features and capabilities. Amazon Lex is a service that enables you to create conversational interfaces with the same technology that powers Amazon Alexa. Google Dialogflow is a platform for building natural and engaging voice assistants for multiple platforms, such as Google Assistant, Facebook Messenger, Telegram, and Skype. Microsoft Bot Framework helps you build and connect voice assistants for various channels, such as Cortana, Skype, Teams, and web apps. IBM Watson Assistant allows you to build and deploy voice assistants for domains like customer service, banking, travel, and health care. Each of these platforms provide different features and integrations with other services like Lambda, Comprehend, Polly, S3, Cloud Functions, Firestore, Translate, Speech, Azure Cognitive Services, LUIS, QnA Maker, Discovery, Text to Speech, and Speech to Text.

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4 How to choose the best voice platform for your project?

When selecting a voice platform for a project, there is no definitive answer as different platforms may suit different needs and preferences. However, there are several factors to consider such as the scope and complexity of the voice assistant, the target platforms and channels, the cost and scalability, the quality and performance, and the support and documentation of the voice platform. For instance, one should determine how many commands, intents, entities, and contexts are needed to handle as well as how much customization is needed for designing and managing dialogs. Additionally, it is important to consider which devices, services, and platforms you want your voice assistant to work with and how easy it is to integrate and deploy. Moreover, one should consider the cost of using the platform's features along with its ability to handle growth in demand. Furthermore, it is important to evaluate the accuracy and reliability of speech recognition as well as natural language understanding along with dialog management speed and text-to-speech responsiveness. Lastly, it is essential to assess how well documented the platform is along with its customer support.

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5 How to get started with voice platforms?

If you're interested in learning more about voice platforms and how to use them to develop voice assistants, there are several steps you can take. Explore the features and capabilities of different voice platforms by visiting their websites and reading their documentation. Try out the demos and samples they provide, and sign up for free accounts or trials to access their tools and services. Follow tutorials and guides to create your own voice assistants, then experiment with settings, parameters, and integrations to customize them. Finally, join forums and communities hosted or supported by the voice platforms to ask questions, share feedback, and learn from other developers.

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Giovanni Toschi

Sr. Director, Artificial Intelligence + Deploying AI agents at scale = Your Guide on the Journey to Automation
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To work effectively with voice platforms, a blend of technical and creative skills is essential. Technically, proficiency in programming (especially in languages like Python or JavaScript), along with a solid understanding of natural language processing and machine learning, is crucial. Knowledge of specific platform APIs and development environments is also important. Creatively, strong user experience design skills are needed to craft engaging and intuitive voice interactions. Additionally, problem-solving abilities and adaptability are key, given the evolving nature of voice technology.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What voice platforms are best for developing voice assistants?

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1 What are voice platforms?

2 Why use voice platforms?

3 What are some of the best voice platforms?

4 How to choose the best voice platform for your project?

5 How to get started with voice platforms?

6 Here’s what else to consider

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