Latest news with #voicetechnology
Entrepreneur
17-07-2025
- Business
- Entrepreneur
United We Care Launches Shunya Labs to Revolutionise AI Voice Infrastructure
The platform supports over 32 Indic languages, including Hindi, Marathi, Assamese, and Maithili. Seven additional languages are currently being integrated. You're reading Entrepreneur India, an international franchise of Entrepreneur Media. In a bold move to redefine the future of voice technology, mental health AI startup United We Care has unveiled Shunya Labs, a deep tech initiative focused on building advanced AI speech infrastructure. Positioned as a game-changer in automatic speech recognition (ASR), Shunya Labs aims to set a new standard in accuracy, speed, and multilingual capability, while maintaining a strong emphasis on privacy and transparency. According to the company, the platform is equipped with an industry-leading ASR engine and real-time, on-premise processing capabilities. Shunya Labs is operational and already demonstrating potential to outperform Big Tech leaders across critical performance metrics. Designed with India's linguistic diversity at its core, the platform supports over 32 Indic languages, including Hindi, Marathi, Assamese, and Maithili. Seven additional languages are currently being integrated. Its use cases span from rural telehealth kiosks to high-demand environments like call centres and defence applications. "We didn't set out to beat the benchmarks — we set out to invent what didn't exist," said Ritu Mehrotra, Founder of United We Care. "And when we built it, we realized we'd created something the world didn't know it needed: AI voice infrastructure that listens like a human, runs like a machine, and respects the sanctity of privacy." Shunya Labs is engineered for efficiency, promising to reduce enterprise cloud expenses by a factor of twenty. It also supports edge deployment, which enables offline functionality and faster inference times, especially critical in remote or sensitive environments. The technology behind Shunya Labs has already shown its capabilities through its integration with Stella, United We Care's AI wellness engine. Stella's foundation in Shunya's ASR technology has led to the creation of a Clinical Knowledge Graph comprising over 230 million nodes and the development of the Spatio-Temporal Graph Attention Network (STGAT), both of which highlight the potential for emotional intelligence and clinical reasoning in AI. "Shunya isn't just a name. It's our origin point — a nod to the Indian discovery of zero that changed mathematics forever," said Sourav Banerjee, Co-founder and CTO. "At Shunya Labs, we start from first principles, engineer with surgical precision, and build for the future — not features. In a world drowning in noise, we build the intelligence layer that actually listens." With plans underway for deployment across multiple continents and an upcoming release on Hugging Face, Shunya Labs is positioning itself not merely as an interface for voice AI, but as the backbone of future-ready infrastructure.
Digital Trends
12-07-2025
- Digital Trends
The 7 best Alexa features you're missing out on
'Alexa, turn on the lights.' In my home, that's one of the most common phrases you'll hear. With a full smart lighting setup all linked to the Amazon Alexa platform and two Echo Show 15s serving as hubs (one in my office, one in the kitchen), the voice assistant is a core part of how I handle everything from lights to groceries. Recommended Videos Most people know about those functions. Making a to-do list, checking the weather, and other day-to-day tasks are how Alexa is used most often, but did you realize the platform has a litany of powerful, lesser-known features? Show and Tell Show and Tell uses the Echo Show's camera to identify products and audibly announce what it is. Aimed at users with impaired vision, Show and Tell is most often used to identify daily items like pantry staples, especially those with labels. For example, it can help distinguish between a container of cumin and a container of cinnamon. Just say, 'Alexa, what am I holding?' or 'What's in my hand?' Your device will guide you through how and where to hold the item, with sound cues to indicate when you have positioned it correctly in front of the camera. Eye Gaze Most interactions with smart assistants are done through vocal commands, but a new feature called Eye Gaze allows users to control specific Alexa devices with only eye movements. This feature benefits people with vocal or mobility impairments, allowing them to trigger pre-set Alexa actions entirely hands and voice free. For now, Eye Gaze is only available on the Fire Max 11 Tablet, and only in a few countries. It's still relatively early in development, but Amazon hopes to bring the functionality to more devices in the future. Real-Time Translation While most people stick to their phones for making video calls, you can also use Alexa to chat with relatives, and she will put captions on the screen in real-time. That makes it possible to hold conversations in multiple languages at the same time, with both sides understanding the other. It also provides assistance to the hearing impaired, as real-time call captions make it easier to follow along if you aren't sure what the other person said. All you have to do is enable call captioning in the Alexa app or in the Echo Show device menu. Adaptive Listening Users that struggle with speech impairments might find they can't get the commands out fast enough for Alexa. Adaptive Listening is a feature that extends Alexa's listening window before processing the request, and it can turned on within the Alexa app or through specific Echo devices. Even people without speech difficulties report utilizing the feature, as it creates a more natural flow to the conversation versus the sometimes clipped language used when speaking with a voice assistant. Find Your Phone I'm scatterbrained, and I will often put my phone down and completely forget where it is. When it comes time to leave the house for any reason, cue a Yakety Sax montage of me checking under couch cushions, the top of bookshelves, and anywhere else I might have left it. Now I can just say, 'Alexa, find my phone.' The device starts a call, and I can listen for the sound of its vibration in the room (my phone has been on vibrate for years). There are also several Alexa Skills available that do the same thing, though I find the default feature works well enough. Whisper Mode When it's two o'clock in the morning and you just managed to get the baby back to sleep, the last thing you want is to ask Alexa a question in a normal tone of voice and wake the baby. Whisper Mode, once enabled, will let you whisper to Alexa and she will respond back in a whisper automatically. The device matches your volume, so you don't need to ask it to respond quietly. Just make sure you enable the setting first. It isn't on by default, and whispering, 'Alexa, what time is?' only to receive an answer of 'IT IS 11:55 PM' at full volume can be jarring, to say the least. Emergency Assist For years, fans wanted Amazon to add the ability for Alexa to call 911. While that still isn't possible, the Alexa Emergency Assist function can put users in touch with a trained 'Urgent Response' agent who can dispatch emergency services. The downside? This feature requires a subscription of $5.99 a month, or $59 per year. Without a subscription, you can have a single emergency contact. With Alexa Emergency Assist, you can have up to 25. It also enables other features and listens for the sound of glass breaking (like a window), carbon monoxide and smoke alarms, and more. Alexa has long been one of the most popular platforms for smart home users, and it only gets better with time. Of course, locking certain features behind a paywall with the Alexa+ subscription slowed its growth, but that's an argument for another day.
Forbes
03-07-2025
- Business
- Forbes
Silent Signals: How AI Can Read Between The Lines In Your Voice
Harshal Shah is a Senior Product Manager with over a decade of experience delivering innovative audio and voice solutions. Voice technologies are no longer just about recognizing what we say; they are beginning to understand how we say it. As artificial intelligence (AI) advances, it can detect subtle emotional signals in our speech, promising more human-like interactions with machines. Emotional AI is reshaping how voice data is used across industries. Think about the last time you spoke with someone who could instantly tell how you felt without you ever saying it. That intuitive recognition is a critical part of how we build trust and empathy. As machines play an increasing role in our lives, they must learn to grasp not just what we say, but how we say it to truly support us in meaningful ways. In this article, I'll explore how AI is learning to interpret the emotional undercurrents in our voices and why it matters more than ever. As someone who has spent over a decade advancing voice and audio technologies across multiple industries, I focus on tuning speech interfaces to detect what people say and how they say it. I have led real-time voice recognition efforts and developed industry guidelines for speech clarity and inclusive interaction. I am passionate about building voice technologies that align with how humans naturally communicate. Understanding Emotional AI And Paralinguistics Have you ever wondered how much your tone of voice says about you? It's not just about the words we speak; it's how we speak them. In my experience, understanding how people talk, their tone, pauses and energy often tells you more than the words themselves. Paralinguistic voice analysis focuses on non-verbal elements of speech like tone, pitch, volume, pauses and rhythm that convey emotion, intention or attitude. While traditional voice recognition focused on transcribing spoken words, emotional AI adds a new layer: interpreting how those words are delivered. Today's AI systems use deep learning to identify these paralinguistic features in real time. Sophisticated algorithms process acoustic data to detect stress, enthusiasm, hesitation or frustration, providing machines with emotional awareness that was once the sole domain of human intuition. Applications Across Industries In digital learning environments, emotional AI can help personalize content delivery. For example, voice-enabled tutoring systems can detect confusion or boredom and adapt the pace or style of teaching. In recruitment, analyzing candidate stress levels or communication style during voice interviews may offer additional insights, though this also raises ethical questions around fairness and consent. In mental health, researchers and startups are analyzing speech patterns to detect early signs of depression, anxiety or cognitive decline. Voice biomarkers can offer a non-invasive, scalable method for screening and monitoring psychological health. In customer service, AI-driven voice systems are trained to adapt based on the caller's emotions. For example, a trained system may detect frustration in a caller's voice. As a result, the case can be escalated to a human agent with specialized training. This emotional routing can reduce churn and improve satisfaction. In safety-critical environments like aviation or automotive, voice systems could be explored to monitor stress and fatigue levels in real time, potentially preventing accidents before they occur. How Emotional AI Works So, how exactly does AI learn to recognize emotions in our voices? At the core of these capabilities is advanced signal processing. AI models analyze pitch contours, speech rate, energy and spectral patterns. Deep learning architectures, such as LSTMs and transformers, are trained on thousands of labeled voice samples to recognize emotion with increasing accuracy. Some models also incorporate context: not just what was said and how it was said, but also when and where. This multimodal awareness, combining voice with video and environmental data, enhances reliability in real-world applications. Ethical Considerations Responsible development of emotional AI depends on a few key best practices. When working with emotional AI, consent is a primary concern. Users may not realize their emotional state is being inferred, particularly if the AI does so passively. Transparency in system design and communication is essential. In light of all of this, championing user consent and clear disclosure when emotional data is being processed is paramount. Bias is another issue. Emotional expression varies across cultures and individuals. AI models trained on narrow datasets may misinterpret non-Western or neurodivergent speech patterns, leading to inaccurate or unfair outcomes. To address this, organizations must audit their models to account for cultural, linguistic and demographic diversity. Privacy is also at stake. Emotional data can be more revealing than words. If mishandled, this information could be used for manipulation, profiling or unauthorized surveillance. To help ensure emotional AI systems are not only powerful but also worthy of user trust, organizations must prioritize on-device processing of data, especially in sensitive contexts like healthcare The Future Of Emotional AI What could it mean for our daily lives when machines start to understand how we feel? Emotional AI is still evolving, but its trajectory is clear. Future systems will combine voice with facial recognition and contextual data to create holistic emotional profiles. These developments could lead to more empathetic virtual assistants, more responsive healthcare bots and safer autonomous systems. However, the future must be guided by principles of fairness, transparency and privacy. As we build machines that listen not just to our words but to our emotions, the responsibility to use that power ethically becomes essential. AI is learning to hear us better. Now we must teach it to listen wisely. As someone who's worked closely with both voice recognition systems and the humans they aim to serve, I believe the goal isn't to replace human empathy but to build machines that can complement it. When used ethically and responsibly, emotional AI has the potential to bridge the gap between data and human connection in powerful, lasting ways. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
