The Power of Voice

The Power of Voice : Audio First Thinking powered by Generative AI

For most of human history people learned and worked by speaking and listening.

Before writing existed, elders passed on knowledge verbally, and even today conversations are the primary way we resolve complex issues. Given the proliferation of other communication forms, voice was and still is our “primary mode of communication” and remains the most natural, spontaneous way to interact. Despite the proliferation of screens, businesses still handle tens of billions of phone calls every day. Legal services, healthcare providers, home‑service companies, and others rely on phone‑based conversations to convey nuanced information, provide personalised advice, handle high‑value transactions and address urgent needs.

Speech is still our default interface. 

Why voice works.

Voice communication is efficient because our brains evolved to process stories and spoken language. When we hear a story, our neurons fire in patterns that mirror the storyteller’s brain; this “neural coupling” creates coherence between speaker and listener. Researchers have also shown that voice lights up more areas of the brain than factual statements and improves memory. Voice engages emotions; the brain produces oxytocin during an engaging narrative. These biological responses make audio feel intimate and trustworthy, explaining why phone calls remain the preferred channel for urgent and complex conversations.

Voice also removes some of the barriers that text‑based interfaces create. PwC emphasises that voice interfaces allow us to speak naturally without learning complicated menus or typing commands. Voice is hands‑free and time‑efficient, making it ideal for busy people. Because we are “voice‑activated”, audio can reach the less tech‑savvy or those with literacy challenges.

The opportunity: audio‑first in a multichannel world

Although we live in a world of texts, emails and social media, audio‑first thinking recognises that voice remains central and asks how to design experiences around it. Businesses increasingly see voice as a way to differentiate because current phone systems frustrate customers: small‑ and medium‑sized businesses miss about 62 % of their calls, calls are sent to voicemail after hours, and people must wait in long queues. Outdated interactive voice response systems from the 1970s offer rigid menu options and usually can’t understand a caller’s intent.

Generative AI radically changes this dynamic. Advances in automatic speech recognition, natural‑language understanding and text‑to‑speech have produced models that deliver human‑like speech across many languages in near zero-latency. These models generate voices with natural pronunciation, stress and intonation patterns and can mimic accents and styles. Thanks to deep learning, synthesized voices are now emotionally expressive and multilingual.

Generative voice models: from text‑to‑speech to speech‑to‑speech

Early voice AI systems used a cascaded pipeline: the user’s speech is transcribed to text, processed by a language model, and then converted back to speech. This approach introduces latency and can strip away emotional cues. The last two years have produced a paradigm shift. Speech‑native models, sometimes called speech‑to‑speech (STS), process raw audio in a single architecture that combines recognition, reasoning, and generation.

Unified STS models dramatically reduce latency and provide more natural, emotionally aware conversations (read more about these here). Voice assistants built on these models can listen, reason, and respond in natural language, mirroring the caller’s tone and handling complex multi‑turn dialogue. These assistants not only answer questions but can also perform actions and integrate with enterprise knowledge bases.

Bessemer Venture Partners observes that new voice AI models produce responses with ultra‑low latency (~300 ms), preserve context from earlier turns, and capture emotional and tonal nuances. Such latency is close to human conversational timing, making interactions feel fluid. The same report highlights that Eleven Labs and other generative voice providers now offer models with unprecedented emotional nuance and cross‑lingual capabilities.

How modern neural architectures and RLHF drive generative voice.

The recent explosion of generative AI for language and audio has been fuelled by breakthroughs in neural network architectures and reinforcement learning from human feedback (RLHF). Both of these architectures are at the core of Instant.Lawyer’s proprietary solutions.

Modern text‑to‑speech systems use deep neural networks to model the complex relationships between text, pronunciation, and acoustic features; recurrent neural networks and transformer‑based architectures learn these mappings and generate speech with natural stress and intonation. Eleven Labs goes further by combining transformers and diffusion models to capture subtle variations in tone and rhythm, resulting in voices that convey contextual understanding and emotional nuance. They are leaders in intonation and rhythm.

On the language side, OpenAI and other providers train large language models using supervised learning on large corpora and then apply RLHF. In this process, human annotators rank or score different model outputs; a reward model—a neural network trained on these human preference rankings—assigns a score to each candidate output, and a separate policy model is then optimized via reinforcement learning to maximize that reward. RLHF ensures that the models not only predict the next word correctly but also align with human values and instructions, producing helpful, safe responses. Because voice agents rely on underlying language models for reasoning, RLHF plays a critical role in making voice interactions feel natural and trustworthy.

The combination of advanced neural architectures and human‑aligned training techniques is what makes today’s generative voice agents expressive, responsive, and safe.

Eleven Labs and the enterprise voice stack

The explosion of voice AI has given rise to specialist platforms like Eleven Labs, which focuses exclusively on audio. According to CEO Mati Staniszewski, Eleven Labs stayed competitive by applying transformers and diffusion models specifically to audio, achieving contextual understanding and emotional delivery. The company-built infrastructure for voice agents and real‑time translation that could eliminate language barriers. Its agents platform provides low‑latency conversational voice agents with advanced turn‑taking, function calling, and thousands of voice profiles.

Eleven Labs is not alone; Amazon’s Nova Sonic, OpenAI’s Voice Engine and Microsoft’s MAI‑Voice‑1 all pursue low‑latency STS models. Analysts expect generative voice models to power a large share of future contact centres; one industry forecast predicts that 75 % of new contact centres will use generative AI by 2028. Specialized voice platforms will remain valuable because enterprises need integrations with CRM and case‑management systems, regulatory compliance, analytics, and fallback logic.

The business value of voice AI

Generative voice technology unlocks tangible benefits for organisations. A unified voice assistant can reduce operational costs by automating routine interactions, improve customer satisfaction through empathetic conversations, serve users around the clock across languages and geographies, enable proactive voice‑based outreach, and empower employees with instant knowledge assistants. Voice remains the channel people prefer; generative AI finally makes it scalable.

For small and medium‑sized firms, the impact will be transformative. With traditional call systems, many calls are missed; AI voice agents can answer calls instantly, handle multiple conversations concurrently and route more complex issues to human experts. In legal services, voice AI can assist with triage, schedule appointments, explain procedural steps and answer general questions in plain language. Because the models support dozens of languages and dialects, they can communicate with clients in their preferred language, improving access to justice.

Challenges and ethical considerations

The promise of voice AI comes with challenges. Generative voice technology can be misused to create deep‑fake audio; dataversity’s overview of AI voice tech warns that voice cloning opens the door to deceptive or malicious uses. Biases in training data can lead to discriminatory outputs, and privacy concerns arise because voice data can contain sensitive information.

Responsible deployment therefore requires transparent data policies, robust consent mechanisms, watermarking to authenticate AI‑generated audio and ongoing bias mitigation. Another hurdle is cultural: some people may find synthetic voices unsettling or may prefer human interaction. As models become more human‑like, organisations must ensure they are used ethically and that users know when they are interacting with an AI system.

Instant Lawyer’s AI agent: talking to you in 50 + languages.

At Instant Lawyer, we believe that voice is the most effective way to make legal assistance accessible. Our AI agent leverages state‑of‑the‑art generative speech models to converse in more than fifty languages. Built on a privacy‑preserving architecture, the agent listens to your questions, develops credible, structured answers, and responds in natural speech, mirroring your tone and style.

It can explain legal concepts, summarise documents and guide you through forms using clear, empathetic language. By removing the friction of typing and reading, we enable users of all backgrounds—including those with limited literacy—to obtain legal information on their terms.

What does this mean in practice?

• Low latency conversations: thanks to speech‑native models, the agent responds within a few hundred milliseconds, making interactions feel natural.
  

• Language and dialect support: generative voice models support and thousands of voices; Instant Lawyer uses models that go beyond baselines to cover over 50 languages and dialects. Clients can speak in their native tongue and hear responses that respect regional accents.
  

• Contextual understanding: the system keeps track of conversation history, allowing multi‑turn interactions and clarifications without repeating information.
  

• Emotional nuance: advanced TTS models can adjust intonation and pace to convey empathy or urgency.

In addition to these technical capabilities, context is central to how Instant Lawyer communicates. Our voice agent delivers legal guidance when users are most ready to hear it. By sensing timing and intent, it ensures messages arrive in the right moment and format, allowing listeners to digest and internalise the information.

Because conversations are replayable, clients can revisit advice in their own environment and share it with family, colleagues, or mentors to deepen their understanding.

Podcasts are a familiar example of how context makes listening powerful; context‑aware voice agents take this further by adapting to each user’s situation and getting smarter over time. When customers can help themselves in this way, it fosters trust and builds stronger client–advisor relationships.

Designing for people with impairments (matters which are very close to our founder's heart).

Voice‑first design also offers a lifeline to people who cannot easily process visual information. Vision loss is widespread: a 2022 Journal of Health Science summarising global eye‑health data estimated that around 1.1 billion people live with some degree of visual impairment, including 295 million people with moderate to severe vision impairment and 43 million who are blind. The same study noted that nearly 89 % of visually impaired individuals live in developing countries. Visual impairment is common even in wealthy nations—according to the U.S. Centers for Disease Control and Prevention, more than 3.4 million Americans aged 40 years and older are blind or visually impaired.

But impairment goes beyond vision. Neurodiversities such as dyscalculia, autism spectrum disorder or attention‑deficit/hyperactivity disorder (ADHD) can make it difficult for people to interpret complex visual cues or stay focused on on‑screen information. There are estimated over 360 million affected by ADHD globally.

An audio‑first interface delivers information through spoken language and allows listeners to replay advice as needed, reducing cognitive load and accommodating different learning styles.

Inclusive from the Ground Up.

By designing Instant Lawyer’s voice ecosystem from the ground up to include people with impairments, we provide a trusted, secure, and efficient way for everyone to access legal guidance. Users can digest advice at their own pace, in their preferred dialect, and share the recording with family members or mentors for further support. This inclusive foundation fosters autonomy, trust, and deeper client relationships.

Voice is not just another interface—it is the interface humans evolved to use. As generative AI brings human‑like speech and reasoning to digital systems, audio‑first thinking allows organisations to build experiences that are intuitive, inclusive, and emotionally resonant.

The convergence of large language models with low‑latency speech synthesis is reshaping customer service, education, healthcare and now law. A focused investment in audio first thinking can produce industry‑leading outcomes.

At Instant Lawyer, we are applying these breakthroughs to customize and democratise legal assistance - enabling anyone to ask questions and receive answers in their preferred language. The power of voice, amplified by AI, has the potential to remove barriers, build trust and open new worlds of possibility.

Peter Toumbourou

on behalf of Instant.Lawyer