Voice Bot Platforms

Voice bots, also called voice-enabled chatbots, are AI-based software that take voice commands and reply by voice. They enable users to communicate faster compared to text based bots. Popular examples of voice bots Apple’s Siri, Amazon Alexa and Google Assistant. There are two types of voice bots:

• Hybrid model: Voice and text controlled bots.
• Voice-only bots: Only Voice-controlled bots.

Like chatbots, voice bots are able to not just recognize what the user says but to understand the customer’s intent and have two-way communication to solve the users’ problems. In addition to the technologies used in text based bots, voice bots also rely on transcription to first get user's commands in text form. They also rely on text-to-speech conversion to talk to users.

Voice bots work like text chatbots. For more information about chatbots you can visit our research on chatbots. An additional voice recognition step is required in voice bots compared to chatbots.

The steps can be summarized roughly:

1-Voice input is taken from the user with a device like a mobile phone or computer with a microphone.

2-This input is sent to the cloud in order to decode the message and understand the user intent.

3-The audio message is converted to text and the natural language processing models analyze the users’ requests.

4- The AI-based engines search for the most suitable answers or actions and create a response.

5-The answer is converted audio and shared with the user.

Using voice bots provide a better, more natural user interface. Companies can use voice bots to reduce call center costs and create more user friendly products.

The increase in mobile users results in an increase in the voice bot demand: Mobile devices provide ease of use in terms of voice applications. It is faster to describe any problem by talking than typing. The progression of speech and voice recognition technologies are supported by tech giants including Google, Apple, Microsoft and Amazon, as well as Baidu, Xiaomi and Alibaba.

Voice-bot adds value to contact centers by reducing queue time and therefore improving customer satisfaction. The problem-solving process of users with call center takes less time than the waiting period. By working 24/7 and with the ability to scale up according to demand, voice-bots eliminate wait times.

The market size is increasing as the demand for chatbots and voice bots: IBM points out that businesses spend $1.3 trillion on 265 billion customer service calls each year. The process can be automated partially by using voice bots.

There are two main reasons why voice bots are preferred to chatbots.

Speaking is a faster way to explain a problem than typing: Especially for older people, typing is slower than talking in describing a problem. On the other hand, according to PWC research, younger people tend to use voice assistants. It shows that voice bots are more useful for both younger and older people in terms of ease of use and faster communication.

People tend to prefer a human-like interaction to tell their problems: Voice bots provide smoother, more human-like interactions

Many tech giants invested in voice technologies in recent years. A disadvantage of voice bot over textual chatbots is the speech recognition time. With the advances in both natural language understanding and speech recognition technologies, launching a voice bot is not significantly more challenging than launching a text based chatbot.

There are four different points to consider while choosing a voice bot provider.

1. NLU capabilities: The NLU infrastructure sets the boundaries of what a voice bot can do. At this point, there may be a tradeoff between price and NLU capabilities. The optimal NLU skills should be chosen by considering the requirements of the use case.
2. Deployment: The training process of AI used by the voice bot must be completed in order to minimize the time required for full integration. Installation of the voice bot into system and without being fully trained can cause problems such as user satisfaction and security. A trained AI can reduce time of deployment.
3. Use cases: It is necessary to determine exactly what purpose voice bot to use. It is necessary to determine exactly what purpose voice bot to use. For example, an IVR bot should not have to have complex NLU. Taking different types of work over the same voice-bot increases the likelihood of errors. Therefore, it may be more suitable to choose an application-specific bot.
4. Pricing: Voice bots have different payment models, just like chatbots. Options such as monthly plan, pay per use, pay per performance may be available. At this point, a payment plan should be selected considering how much the boat will be used. However, in most cases performance-oriented payment plans may be a viable option.