Voice recognition software market to hit $10.5 billion by 2030
The global voice recognition software market, valued at USD$3.5 billion in 2021, is estimated to grow to reach more than USD$10.5 billion by 2030, at a CAGR of 20.12%, according to ew forecasts from Regional Research Reports.
Voice recognition technology is impacting every aspect of how businesses communicate with people. Although voice recognition technology is still in the early days, it has grown and developed in leaps and bounds.
Voice recognition technology — also known as digital assistants, virtual assistants, virtual agents, interactive agents, and more — has gone from being a simple conversational interface where the user would input text and receive a canned response, to a robust tool where users can converse with a computer via text or voice and receive bespoke responses based on the given context.
This advancement is due largely to the rise of artificial intelligence and natural language processing (NLP) software, as well as improvements in computing power.
However, the rise of voice recognition technology should not be viewed in a vacuum. Messaging, in general, has arisen as a preeminent form of communication, and as such, it should come as no surprise that people want a faster and more accessible way to get information. Voice recognition technology can get information quickly and can help companies fulfil this desire.
With the use of machine learning and deep learning, voice recognition technology can grow intelligently and understand a wider vocabulary and colloquial language, as well as provide more precise and correct responses to requests. Through providing information and conducting specific tasks, whether external, customer-facing requests or internal, employee-facing requests, voice recognition technology can augment humans’ abilities.
Voice Recognition Software Market Pricing
Voice recognition technology software pricing is estimated to range from USD$100 to USD$350. The pricing depends on the features and specifications integrated into the software. The main features for the software include emotional intelligence, conversational ability, broad knowledge base, personal, and personality.
Any software can come with its own set of challenges. Voice recognition technology, which is changing many industries and use cases (such as customer support and e-commerce), has some key issues which organisations should keep in mind.
Preference for human agents: Although voice recognition technology is great at many tasks, some contexts, such as those which require a significant amount of empathy, may be better served by a human agent.
Handoffs to humans: There might come a time when voice recognition technology does not have an answer to a question from the user. It is critical that the system is designed in a way to successfully resolve this problem. Typically, the best way to solve this is to transition the user to a human agent.
In addition, artificial intelligence techniques such as NLP software help make voice recognition technology solutions easier to use and more powerful, providing more accurate results. Below are the trends relevant to this software.
In general, users are looking to conversational interfaces to get answers to their burning questions. For example, they are looking to query their data in a more natural way. Since natural language understanding has improved, people can talk to their data, finding and exploring insights using natural, intuitive language. With this powerful technology, users can focus on discovering patterns and finding meaning hidden in the data as opposed to memorising SQL queries.
Data-focused businesspeople, like data analysts, can benefit from conversational interfaces like voice recognition technology. Users can uncover the material they are looking for using intuitive language. Intuitive methods of querying data mean a larger user base that can access and make sense of company data.
Voice is a primal method of interacting with others. It is only natural that we now converse with our machines using our voice and that the platforms for said voicebots have seen great success. Voice makes technology feel more human and allows people to trust it more. Voice will prove to be an important natural interface that mediates human communication and relationships with devices, and ultimately, within an AI-powered world.
AI is quickly becoming a promising feature of many, if not most, types of software. With machine learning, end users can identify patterns in data, allowing them to make sense of content and help them understand what they are seeing. This pattern recognition is fuelling the rise of more powerful, contextually-aware voice recognition technology.