Why businesses need voice assistants and what they will become in the future

What are speech technologies and how do they work

Speech technologies are technologies based on machine learning. They are divided into two directions: speech synthesis and speech recognition. Synthesis is the conversion of text into audio, while recognition is the reverse, converting audio into text.

A neural network is trained on data fed into it. There are various technical quality indicators for speech recognition: WER, throughput, the ability to fine-tune, and others. In practice, the quality of a model can be assessed by how well it adapts to specific topics: medicine, industry, finance.

What artificial intelligence is responsible for in voice assistants

Artificial intelligence can recognize context and the nature of the conversation: whether there is negativity, whether certain dates are mentioned, for example, when booking a doctor's appointment.

This is important both during the operator's conversation with the client and for further analysis. Yandex Cloud presented the Yandex SpeechSense speech analytics service: it allows for detailed analysis of contact center operator calls and chats, including assessing their tone and engagement in dialogues.

Models can also automatically detect language, which is especially important in countries where multiple languages are spoken. Yandex's speech technologies, used in Yandex SpeechKit, allow understanding mixed speech, where words from different languages are used in a single sentence, as well as synthesizing multilingual speech using the same speech model.

Who are the customers of speech technologies

Speech technologies allow improving customer experience, increasing sales, and enhancing the quality of contact center operations. Specific scenarios include outbound telemarketing campaigns, informing about appointments, cross-selling products and services. Therefore, customers are usually business units.

Traditionally, the main driver of technology development is financial organizations: banks, payment gateways, crypto exchanges. They need technological solutions to increase security, speed up transactions, make services more user-friendly, and thereby gain a competitive advantage.

Companies with high contact center loads also actively use speech technologies. For example, more than 50% of inquiries to airline support concern flight status. Responses to such inquiries can be automated.

How quickly do investments in speech technologies pay off

If the technology is implemented correctly, returns can be seen quite quickly. At the same time, companies often view this as an investment in the future: even if it does not pay off within one to three months, over several years the solution will begin to generate additional profit. Plus, such effects as increased brand loyalty and recognition are harder to measure in monetary terms than indicators like ROI and TCO.

It is also important that the entry barrier is decreasing, and implementing speech technologies no longer requires such large investments as before. With a cloud solution, you can test hypotheses with minimal investment and scale them in case of success.

What results does the implementation of speech technologies yield

According to our statistics, voice robots reduce the load on the contact center by at least 30%. With the addition of speech analytics, the conversion rate of a single conversation can be increased by tens of percent by providing the right scripts for sales managers during the call.

How speech technologies are developing in the Kazakhstan market

Many Kazakhstani companies are developing and successfully implementing speech analytics and voice robots. The quality of these solutions is also growing: a good recognition and synthesis engine, which forms their basis, is the key to success.

If earlier only large companies could afford such robots, now the entry barrier is so low that even a small taxi fleet can automate incoming calls, distribute them among drivers, and quickly see the economic effect.

In Kazakhstan, popular scenarios include automating the first line, telemarketing campaigns, and satisfaction surveys.

Large companies are also working on their own unique speech models. I think in 2024 we will hear new voices that will be associated with certain brands.

How will voice assistants develop in the coming years

The quality of synthesis and recognition will improve. Robots will become more flexible in scenarios with users: they will be able to be cheerful, sad, speak in whispers, use slang, and fully adapt their communication style to a specific user.

Trust in voice assistants will grow: if earlier users immediately asked to be transferred to an operator, gradually more questions will be resolved faster with a robot. As one of our clients says, a good robot is much better than a bad operator.

Which IT specialists in the field of speech technologies are in demand today

Traditionally, demand continues to grow for developers, ML, and DevOps specialists. Also, projects involving speech technologies must necessarily include analysts, Project managers, and editors who work with scripts.

Specialists who combine different competencies: business analyst, consultant, marketer, IT specialist, and also understand financial indicators will become in demand.