Artificial Intelligence (AI) and Natural Language Processing (NLP) enablement in consumer devices are fueling the shift toward voice applications. Connected devices such as smart automation consoles, home appliances, TV, and speakers make voice assistants more useful to users. Early adopters and technology leaders are focusing on enabling their next-gen own voice technology integrations to keep pace with consumer demand.

There is an exponential growth in the adoption and implementation of voice interfaces in every industry.

Few Applications Areas

Healthcare: During the pandemic, AI-powered chatbots and virtual assistants played a vital role in the fight against COVID-19 by making health services more accessible while lowering the risk of COVID-19 exposure. With patients’ mindsets shifted, we can see more openness and acceptance for using telehealth and remote diagnostic services.

Retail and Banking: Virtual assistants and voice-enabled intelligent kiosks can help customers with the necessary information and product suggestions. It can also guide users with self-checkout and payment transactions.

Home Appliances and Smart HMIs: Integrating voice tech into mobile apps and home appliances has become the hottest trend right now and is expected to remain so because voice is a Natural User Interface (NUI). Voice assistance is a key component of smart speakers that use voice recognition, NLP, and speech synthesis to assist users with tasks like music selection and playback.

Technology Trends

Mobile App Integration: Voice-powered apps increase functionality and save users from complicated app navigation. Voice-activated apps have also simplified interaction for young kids or elderly people having a limited vision.

Voice Search: Brands are now experiencing a shift where touchpoints are transforming into listening points, and organic search will be the main way for brands to have visibility. Search behaviors have seen a huge shift from touch to voice as most consumer devices are getting smarter and enabled with voice search apps. It is expected that voice-based ad revenue could reach $19 billion by 2022.

Individualized Experiences: So far the focus was on understanding commands. Now, the focus is on voice recognition to offer more individualized experiences as they get better at differentiating between voices. Google Home can support up to six user accounts and detect unique voices, which allows Google Home users to customize many features. Users can ask, “What’s on my calendar today?” or “Tell me about my day,” and the assistant will dictate commute times, weather, and news information for individual users. Similarly, for those using Alexa, simply saying, “Learn my voice” will allow users to create separate voice profiles. So, technology can detect who is speaking for more individualized experiences.

Voice Cloning: Machine Learning tech and GPU power development commoditize custom voice creation and make the speech more emotional, which makes this computer-generated voice indistinguishable from the real one.

Several industries are looking to adopt voice technology; however, a lack of skills and knowledge makes it particularly hard for companies to develop a strategy. One needs to overcome several barriers to the mass adoption of voice applications. However, AI and NLP are key technology enablers. With consumers becoming more comfortable with using voice commands, voice technology is likely to become a primary interface. That entails a greater demand for tools and expertise for voice interface design and voice app development.

Key Technology Enablers

Voice technology is becoming increasingly accessible to developers. Technology leaders like Amazon offer Transcribe, an Automatic Speech Recognition (ASR) service that enables developers to add speech-to-text capability to their applications. This helps application developers in getting a text file in return for the voice file for appropriate action.

Google has made moves in making Assistant more ubiquitous by opening the software development kit through Actions that allows developers to build voice into their products that support artificial intelligence.

Another one of Google’s speech-recognition products is the AI-driven Cloud Speech-to-Text tool that enables developers to convert audio to text through deep learning neural network algorithms.

If we look at the underlying hardware, many platform companies are also proactively coming up with hardware features and software SDKs to enable these solutions. For example, Qualcomm® Voice Assist enables next-gen voice user interaction capabilities with low power voice wake up, advanced AI-based speech recognition, and dedicated audio hardware. Low-power Audio Subsystem (LPASS), part of the Qualcomm AI Engine, is purposely built for audio processing and is a combination of multiple scalar DSPs and other audio-related hardware that does everything virtually, from audio coding/decoding, voice verification for security features, to audio speech recognition and machine learning.

Qualcomm Snapdragon 855, QCS 605, and QCS 405 are a few examples of application processors that support Qualcomm Voice Assist technology.

Being a Qualcomm technology licensee, eInfochips has access to these platforms and offers modules and development kits to kick-start product development. eInfochips has developed an intelligent video conferencing soundbar based on Qualcomm QCS605 and QCS 405. We also have experience in developing multiple products based on Qualcomm’s ultra-low power, and premium-tier Audio SoCs including QCC3031, QCC3026, and QCC512. To know more about our offerings, please contact our experts.