It all started with the Audrey system that was created by Bell Labs in 1952. Initially, it could only recognize spoken digits. Since then we have never stopped advancing voice technology. The Internet of Things (IoT), which connects billions of physical devices for the convenience of people, has become a key factor driving the spread of Voice AI.
The growing popularity of the Internet of Things and modern AI technologies are giving birth to a new ecosystem of companies in the current and post-COVID world. This leads to increased scrutiny of privacy and monetization strategies that exploit consumer private data.
Nevertheless, voice artificial intelligence raises some concerns. Shoshana Zubof, a professor at Harvard Business School, calls voice technology surveillance capitalism and argues that voice-enabled devices and AI, among other data-gathering tools, are leading to a single voice: one that provides its operator with the ability to anticipate and monetize people’s desires.
Thus, two main trends underlie the breakthrough of the voice analytics sector, namely:
- implementation of IoT and cloud technologies using AI and machine learning;
- advances in psycholinguistic data analytics.
How does voice technology enrich people's lives?
The media, influential leaders in the technology industry and governments continue to lead discussions about AI and its impact on humanity. However, it's hard not to notice the importance of voice technology in symbiosis with artificial intelligence, as well as how it enriches the lives of consumers.
So far, voice technology has given people the following key benefits that will be actively developed in the future:
- home automation;
- simplified text input mode using voice;
- smart voice bots for customer support and service.
Buying by voice is predicted to grow to billion by 2025. The latest study shows that almost three-quarters of people who own devices with speech recognition say they’re indispensable in everyday life.
In the future, gaining consumer confidence will be paramount. Therefore, those corporations that actively begin to implement Privacy by Design will gain a competitive advantage in order to guarantee the protection of personal information in systems based on voice technologies.
In addition, the wider adoption of Edge Computing and the rollout of 5G networks will dramatically change the availability of voice-enabled products. Because these advances will result in the data generated by voice-enabled IoT devices being processed at the source itself.
Voice technology is changing business
While audio and video chats for business meetings have already been gaining popularity in the last 10 years, the coronavirus has accelerated their use. Did you know that 200 million Microsoft Teams meeting participants interacted in a single day in April 2022 and generated over 4.1 billion meeting minutes?
Voice-enabled chatbots are being used by call centers to increase efficiency, and the current environment ensures that these digital technologies may well replace tasks performed by humans.
In other areas, the relationship between natural language processing (NLP) and artificial intelligence blurs the lines between people and technology. For example, physicians are increasingly relying on the use of AI, which converts voice-dictated clinical records into machine-readable electronic medical readings. In combination with the analysis of diagnostic images, this can greatly simplify the diagnosis of neurological and cardiac diseases, cancerous tumors.
AI and Machine Learning in Psycholinguistics
The study and application of human speech has grown dramatically due to the integration of computational linguistics with affective computing thanks to AI and ML technologies. Companies and researchers are developing new scalable approaches for automatic speech recognition.
For example, Google used neural network language models, linguistics, and experimental psychology combined with rigorous data analysis to create a speech analysis platform. It transcribes the audio and displays its data using infographics. Any call is sorted by key indicators, which include duration and tone.
Potential leaders in the use of voice technologies are the media and the entertainment sector. They have already prepared consumers for what reality could be in the future by demonstrating artificial intelligence-based digital assistants replacing human beings.
There’s a quasi-real movie, called Her, where the main character Joaquin Phoenix talks to Samantha, who is a voice assistant. Such communication fulfills Joaquin’s need for companionship. This context seems quite applicable to the fact that humanity is currently facing social distancing and isolation caused by the coronavirus.
From a technological standpoint, AI algorithms form the basis of Samantha's "humanity" as she analyzes speech, emotions, and intentions. These same algorithms are accelerating the adoption of streaming services. Investing in content from industry-leading companies like Netflix, Amazon Prime, and Disney+, as well as well-funded startups like HBO Go and Quibi, are great for leveraging AI and ML built on top of voice analytics.
Voice Technology Research
Academic research has become fertile ground for bringing together NLP, AI, and psycholinguistic data analysis for business applications. For example, Deborah Estrin, a professor from Cornell Institute of Technology who received a MacArthur Genius Grant in 2018, is studying how podcasts can be measured to predict their popularity.
The stakes for voice analytics in a booming sector are high. In 2021, podcasts generated 0 million in ad revenue. Whereas Spotify spent 0 million to expand audio content in 2021.
Lyle Ungar from the University of Pennsylvania together with his team scanned millions of social media posts with audio content to identify different audio signals using machine learning. In this way, they tried to structure the language and the types of words used, which may indicate a mental disorder or cognitive problems.
This will help to use AI and voice technology to solve financial crimes, manage customer risk and reduce the cost of doing business.
Voice analysis of functional words, like pronouns, articles, prepositions, conjunctions and verbs, which are the connective tissue of the language, offers a deep understanding of a person's honesty and sense of self. This allows you to find out his emotional state, personality type, age and social class.
New methods study how words are pronounced and look at non-functional words such as vocal bursts to identify emotion. Evidence of the importance of the link between AI and consumer behavior is the Technology and Behavioral Science Research Initiative at the Wharton School.
Voice technology could expand to the point where there would be a universal translator that would cover hundreds of the world's languages, including local dialects.
This direction has great potential, as it opens up new horizons for consumers.
There’s already Microsoft Translator with advanced AI capabilities and deep neural networks. The company announced that the program will soon offer real-time translation into five additional Indian languages. This will bring the total number of languages to ten, allowing 90% of Indians to access information in their preferred languages.
The Universal Translator, first described in Murray Leinster's novel First Contact, may very well become a reality.
A traditional problem for niche languages has been the lack of an adequate dataset for training AI platforms. New methods, technologies and psycholinguistics make it possible for rare languages not to have so many formal linguistic tools to be explored. For example, the Rochester Institute of Technology is using deep learning artificial intelligence to create audio and text documentation in the Seneca language, which is spoken by fewer than 50 people.
However, the accuracy of spoken identification requires constant investment in representative datasets, models, and artificial intelligence technologies. Studies show that Google's speech recognition has an accuracy rate of 78% for Indian English and 53% for Scottish English. In addition, the voice search engine is 13% more accurate in determining the queries of men than women.
Artificial emotional intelligence
It’s predicted that voice technology will become the main tool in the field of artificial emotional intelligence and will allow for a more detailed study of human emotions. As the voice environment becomes a natural way for people to interact, this will lead to improvements in measuring intent through voice recognition and voice analytics.
The efficient computing market is estimated to grow to billion by 2029. Contributing to IEI will lead to a shift from highly intelligent data-driven interactions to deep experiences powered by the emotion equalizer, enabling brands to connect with customers on a much deeper and more personal level. The accuracy of detecting human feelings will be greatly improved.
AEI is expected to combine voice with visual and biometric sensors and other data to support emotional AI applications. They, in turn, will offer better customer service.
Understanding the importance of AI voice, its analytics, impact, risks and possible future direction, one can take a broader picture of digital innovation as a whole. Modern voice-based AI technologies can offer many benefits to society and business, but the negative consequences associated with this need to be carefully considered.
More broadly, perceptual AI that spans the entire sensory spectrum, including sight, smell and touch in addition to voice, could lead to more humanized technologies that will revolutionize how companies and consumers interact with products.
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