Aug 13, 2021, inside iteo, Web

Hellobot – iteo’s voice solution functional review

Karol Świderski Junior .NET developer
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The world of today’s tech enables having a casual phone call using varied voice technologies. They allow substituting a human voice in conversations characterized by repeatable questions and answers. Thanks to iteo’s voice solution, Hellobot, user’s queries can be comprehensively processed, providing a wide range of AI-based functionalities and integrations with various systems.

A few words of introduction

Our clients can use many different functions which improve their conversation with a bot and allow them to carry out complicated scenarios compatible with a company’s business assumptions. Voicebot is a great match for a lot of diverse branches. Its only limitation is a clients’ creativity, but they’re always supported by a team of experienced developers.

The basis of every conversation with a bot is a proper scenario. Its level of complexity depends mainly on business goals we want to achieve. It can be compared to a decision tree. Each question asked by a bot and each answer provided by a user moves a speaker further, through subsequent components called actions which apply to different matters. They cover basic abilities of talking and speaking, recognizing intentions, extracting entities, carrying out HTTP queries to varied external systems, as well as GDPR messaging, redirecting a call or reporting conversations’ results. The modularity of creating scenarios allows reusing some of the repeating elements which has a great impact on shortening the time of implementation.

Exemplary scenario diagram

A wide list of Hellobot’s functionalities and abilities allows placing the solution in the category of advanced voice systems, enabling complex speech processing. The most essential functions include:

  1. Speaking and listening
  2. One statement – many pieces of information
  3. Unique conversation
  4. Address verification
  5. Payment handling
  6. Sex recognition
  7. External REST API integration

1. Speaking and listening

It’s every voice solution’s basic task – its correct implementation and usage are the first step to a scenario’s success. 

In particular moments of conversation a bot says specific, predefined statements prepared by a specialist. They can have any content and length. Main tools used to achieve this goal are Google Text-to-Speech and Azure Text-to-Speech which provide a similar set of functionalities: spelling, reading dates, taking a break while speaking, and many more. Creators can use provided parameters such as: talking speed or a type of voice. An unquestionable advantage of both solutions is Polish language, reasonable price and certainty of developed tools performance.

An answer given to a bot is extremely important and Google Speech-to-Text is a speech recognition tool that brings the best results. Thanks to its flawless work, speech-to-text conversion ends with a full success which has a huge impact on the whole conversation.

2. One statement – many pieces of information

Nowadays, formulating and asking a question, and then recognizing the answer correctly is not enough. A user talks to a bot to solve a certain problem which requires adequate understanding and interpretation of acquired information. To meet clients needs, Hellobot is equipped with proper AI mechanisms provided by a wit.ai tool. They allow categorizing the statements and extracting particular information. 

The diagram below shows acquiring two pieces of information about a pizza: ‘size’ and ‘type’. Additionally, the voicebot asks about ‘dough’ because this information is lacking. In the second example, there’s no information about the ordered food, so the bot asks general questions.

After preparing the wit.ai application context and a correct network training, a user’s statement can be categorized to extract the relevant information which has an actual impact on the whole conversation. By designing a conversation scenario properly, one can acquire many pieces of information at the very beginning of the talk which allows us to significantly shorten the order process. As a result, the conversation with the bot becomes more natural, because it gives an impression of the machine understanding the speaker’s needs and saving acquired information. One simple question: “Hi, how can I help you?” makes the conversation more open and casual than a linear scenario built from many schematic questions.

3. Unique conversation

The main reason people often avoid talking to bots is the perception that they are dull and monotonous, particularly when repeated conversations are required to resolve an issue. This repetition can lead to aversion, as users hear the same statements repeatedly. To address this, the Hellobot team has developed a feature that enhances customer service by enabling unique conversations. By utilizing natural language processing and natural language understanding, the bot’s creators can design multiple versions of responses that appear randomly, thus significantly reducing the monotony of interactions.

This innovative use of technology ensures that each conversation with the bot remains fresh and engaging. The extensive database of varied statements ensures that the likelihood of exact repetitions is low, improving customer satisfaction. Moreover, the integration of automatic speech recognition helps the bot understand and process voice commands more accurately, facilitating smoother and more natural conversations. This approach not only improves the customer experience but also anticipates the needs and responses of users, making the interactions as helpful as those with a live agent.

Furthermore, the implementation of machine learning allows the bot to learn from past interactions, continuously improving its responses and becoming more adept at handling complex customer interactions. This self-service model, supported by smart speakers and voice assistants, offers users a hands-free and efficient way to solve their problems, enhancing the overall customer journey. Hellobot’s approach to designing bot conversations with an emphasis on variety and learning capability marks a significant step forward in transforming how voice bots are perceived and used in daily interactions.

4. Address verification

This functionality brings a totally new light to our voice solution. During a conversation, Hellobot is able to recognize an address. Its correctness is validated with the use of Azure Maps. If the address is correct, the bot continues the conversation. In case of any errors or lacks, it can ask for missing parameters – a street or a building number.

This functionality can be used in many different situations. Recognizing the address correctly and having it saved allows determining the place of meeting or delivery, and the implemented validation excludes potential errors or misunderstandings.

5. Payment handling

In the times of pandemic, a possibility of limiting unnecessary contact with other people is extremely important and highly valued. That’s why Hellobot is equipped with mechanisms that allow processing online payments. Such a solution is valid in many everyday situations like paying for an order or the amount due. And the process is super easy. When users decide on an online payment, the bot sends an SMS with a link to their phone. By clicking it, a payment can be made by using the most popular online tools. In this case, money goes straight to the receiver which significantly increases the convenience of use. 

6. Sex recognition

The bot is able to determine what is the sex of the speaker based on his or her statement. It makes the scenario more personalized, because a user hears properly inflected sentences. Verification is based on the statement’s transcription. It allows excluding improper sex recognition of a man with a high or a woman with a low voice. 

7. External REST API integration

During customer interactions, Hellobot leverages external REST API integration to fetch data in real-time from client systems using HTTP queries. This allows Hellobot to provide indispensable information conveniently and efficiently. External REST APIs are crucial in cases where dynamic and responsive communication is needed to enhance customer service. The process is a sophisticated example of natural language processing and understanding, enabling the bot to tailor conversations according to specific user data. This integration supports a two-way communication model, where Hellobot not only receives data but can immediately inform the client system about the outcomes of interactions, ensuring that customer needs are met promptly and accurately.

The application of machine learning algorithms in this context allows Hellobot to learn from each interaction, improving its responses over time and increasing customer satisfaction. The integration of automatic speech recognition technologies enables voice commands and natural conversation features, particularly beneficial for voice bots and voice assistants used via smart speakers. This approach not only streamlines self-service processes but also provides seamless hand-offs to live agents when necessary, further enhancing the overall customer experience. By incorporating these advanced technologies, Hellobot is able to handle critical processes dependent on the conversational scenario, ultimately optimizing operations and customer interactions.

Summing up

Hellobot leverages advanced artificial intelligence to facilitate natural conversations, analyzing and interpreting user statements with precision. Its implementation incorporates cutting-edge technologies such as natural language processing (NLP) and automatic speech recognition (ASR), enhancing its ability to handle various customer interactions seamlessly. The scalability of Hellobot allows it to process numerous calls simultaneously, managing constant loads effectively and ensuring a robust customer experience.

By integrating solutions from the best external companies, Hellobot efficiently handles complex scenarios across different everyday life branches. Its modular design not only shortens the overall process time but also facilitates continual adaptation to market demands and the latest trends in the voice technology industry, including voice commands, voice bots, and smart speakers.

Hellobot’s capabilities are further enriched with natural language understanding (NLU), allowing for more accurate and natural conversation experiences. This technology is pivotal in enhancing customer service, enabling both self-service options and smooth transitions to live agents when necessary. Through the use of machine learning, Hellobot continuously improves its interaction models, thus enhancing overall customer satisfaction.

In summary, Hellobot is a sophisticated voice assistant that not only responds efficiently to voice commands but also significantly improves the quality of customer service, adapting dynamically to new developments in the field and enhancing user engagement through smart and responsive communication.

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