There is no such technology as interfaces based on voice and gesture that appeared yesterday or even a few years ago. Such interfaces have existed for many years. The first voice recognition system that could recognize numbers when uttered by a single voice was revealed by Bell Labs in 1952, and this was the starting point for voice-based interfaces. Software from a company known as Dragon Dictate, which allowed dictation of text using one’s voice, was later released in the 90s following the release of the first commercial speech recognition technology by IBM in the 70s.
In the gesture-based world, things began in 1982 when the first touch screen came into existence, which was capable of allowing human touches made through fingers to be used in communicating with a computer. Nintendo’s Power Glove, which offered gamers a gesture-based input device in the gaming engine, came out in the 90s.
While these technologies have been gaining popularity on their own for the past few years, the promotion of AI and machine learning has brought these interfaces to a new level, even if they have not been forgotten. These interfaces are getting much more sophisticated and friendly to the user as they can parse spoken language and recognize trends in gesture identification. In addition, they offer several advantages over traditional interfaces, including the ability to deliver more individualized experiences, improved accessibility to disabled individuals, and hands-free operations.
What is an AI voice?
AI voice is a technique that uses deep learning models built on actual voice data to mimic human-like speech from text inputs or other sources. It produces realistic-sounding voices that may be altered according to emotions, accent, age, and gender.
AI speech enables you to manage large call volumes, automate customer care, and deliver consistent service quality throughout all client encounters using voice bots and IVR systems. Without human assistance, contemporary AI voice technologies can comprehend user intent, assess speech context, and produce relevant responses.
The interface of voice and gesture AI
Speech recognition and natural language processing are two important considerations since they are essential for voice-based interfaces. Complex, complication- and confusion-prone commands and interfaces that can identify numerous languages, accents, and dialects should be created. When evaluating these technologies on small, homogeneous populations, it is easy to fall victim to prejudice, which makes the designs vulnerable to ambiguity and new information. Even more so than in design in general, user testing and focused user research are essential while developing new technologies.
Knowing who your end users are is crucial. To master a certain subset of languages and dialects before expanding, think about localizing your voice interface at the beginning if that demographic is large. To guarantee the precision and efficacy of your customized voice interface, collaborate with regional experts and language professionals.
Designers of gesture-based interfaces must consider how users will interact with the interface and create simple, intuitive motions. Determine the situation in which the gesture-based interface is to be used. To come up with gestures that are appropriate and efficient in the context of use by the user, the designers consider the environment, position, and posture of the user, as well as the tasks the user will be executing. The position of a phone in the hand is a common one. The main functionalities should be accessible within the bottom two-thirds of the screen, as most thumbs in this position can only reach those points. The thumb cannot reach anything over the bottom two-thirds of the screen; to do so, one must change the position of their hand.
How do AI voices and gestures work?
The main function of AI voice technology is to translate human speech or text into spoken language that sounds natural by utilizing a few essential elements:
1. Automatic speech recognition
In the first step, the system records an audio snippet using a microphone and splits it into small pieces (10–20 ms) then changes them into spectrograms, graphic representations of sound frequencies over time. These spectrograms are then put through deep learning models, which then convert the spectrograms into text using the identification of phonemes, or basic speech sounds. To increase accuracy, ASR also reduces background noise and adapts to various dialects and speech rates.
2. Natural language processing
Speech-to-text conversion is followed by text analysis using NLP to determine the user’s purpose. It deconstructs phrases both syntactically and semantically, identifies named items (such as names, dates, and locations), categorizes intent, and uses sentiment analysis to identify emotions like joy or dissatisfaction. This enables the system to react appropriately and sympathetically.
3. Data management
Using confidence scores to determine what to ask next or when to complete tasks, this component keeps the discussion moving by keeping track of user knowledge and context. For instance, the system requests clarification before moving forward if a date is not apparent when making a reservation.
4. Text-to-speech (TTS)
TTS translates the text back into spoken words after the system has produced a response. AI voices now sound incredibly realistic and human-like due to modern TTS, which models language, acoustics, and prosody to create authentic intonation, rhythm, and expression.
5. Speech-to-speech and voice cloning
AI voice systems are also capable of voice conversion, which involves taking human speech as input and altering it to sound like the voice of another person. They can also translate speech between languages while maintaining the identity of the speaker.
Importance of voice and gesture in AI
Users with disabilities, including blind or those who have mobility issues, may prefer voice- and gesture-based interfaces. For example, an individual with limited mobility can perhaps control a gadget without the use of his or her hands using a voice-based interface. It is important to ensure that these interfaces can be usable by all and that accessibility factors were taken into consideration during their development.
To ensure that you are accommodating multiple abilities and preferences among the users, you must provide several methods of input, such as text, voice, and gesture. Furthermore, multi-modal feedback is required. When thinking about feedback for a significant user action, examine all of the feedback systems that a solution like Apple Pay uses to guarantee accessibility. Along with a haptic vibration, an audio notification that dings, and a graphic on the screen confirming payment, the user will also receive a push notification with the charge amount. To make sure that every user is getting confirmation of their activities, all of these forms are for feedback.
Future challenges for voice and gesture in AI
Although voice- and gesture-based interfaces have many advantages, designing for them presents certain difficulties. The following are some typical mistakes made when creating these novel interfaces:
- Confusion and annoyance can result from voice- and gesture-based interfaces that don’t give the user feedback. For instance, the user may be left wondering if the voice interface comprehended their instruction if it does not provide audio signals or confirmation messages when a command is recognized.
- In so many of the designs we encounter daily, we have come to embrace a multitude of design principles. In this era of voice- and gesture-based interfaces, it will be crucial to rigorously design a new set of standards to produce satisfying user experiences.
- A user may find a gesture-based interface that necessitates intricate or counterintuitive motions annoying, and it may be difficult to learn across devices and other goods.
- Concerns regarding security and privacy may arise from voice interfaces that are constantly listening.
- Voice assistants, for instance, have been known to capture private conversations and send them to outside businesses for research. The loss of trust between consumers and these products lies at the heart of this problem.
In the field of UX design and product development, voice, and gesture-based interfaces are a fascinating trend with many advantages over conventional interfaces. Product designers must keep abreast of these new developments and consider how they could enhance our products’ user experiences. With the correct strategy, we can design fun user interfaces that are easy to use and accessible.
Oxford Premier Center offers a wide range of Artificial Intelligence (AI) Courses, including specialized programs in AI for managers, technical professionals, and software developers, as well as short courses in data science, robotics, and low-code AI applications. By leveraging these educational opportunities and the correct strategy, we can design fun user interfaces that are easy to use and accessible.