Unlocking the mysteries of voice
TelltaleTM Voice Intelligence Platform
Where voice intelligence
goes to work
Security & Law Enforcement
Match a voice with an individual, or search for an individual by voice. Build a scene description and speaker profile from forensic recordings.
Finance & High-Value Industries
Verify callers and catch synthetic (“deepfake”) or altered voices.
Gaming & Social Media
Check age and identity on a platform, and spot banned users who come back. Flag harmful speech in multiplayer voice chat, and protect young players.
Automotive & Consumer Electronics
Know who is speaking to a car or device, and what state they are in.
The human voice carries more information than any other human signal.
Your voice carries your identity
Every human voice is a unique, time-varying biometric that encodes identity, state, and surroundings.
Our work is to read that signal — rigorously, reproducibly, and responsibly.
Team
Caleb Castillo spent his career in venture capital and private equity before co-founding Human Voice Inc., and now leads the company’s strategy, partnerships, and capital formation.
Dr. Rita Singh founded the Center for Voice Intelligence and Security at Carnegie Mellon University, where she also co-leads research groups in Machine Learning for Signal Processing and Robust Speech Processing. With over two decades of experience in speech and audio, she began specializing in voice-based human profiling in 2014—a unique intersection of AI and Voice Forensics. Under her leadership, her team demonstrated the world’s first voice-profiling system at the 2018 World Economic Forum. In 2019, they achieved the unprecedented voice reconstruction of Rembrandt using facial evidence, and in 2020, they created the first voice-based COVID-19 detection system. Author of the 2019 Springer-Nature book Profiling Humans from their Voice, Dr. Singh frequently assists international agencies with investigative voice evidence analysis. Her groundbreaking contributions have been featured in hundreds of print and online articles worldwide.
Dr. Anders Øland wrote his first computer program at age 10 and read his first book on neural networks at 15. He holds a bachelor’s degree in software development and earned his Ph.D. from Carnegie Mellon University, where his research focused on efficient deep learning and on applying AI and machine learning methods to problems in music production and speech. Professionally, he has worked on cutting-edge deepfake systems for Hollywood, and on conversational AI agents for heavily regulated industries. He is named as an inventor on multiple U.S. patents, and he’s also an award-winning music producer.
Brad Warren is a technologist whose career has spanned law enforcement, military operations, and artificial intelligence. He’s served as a hostage negotiator and detective, has worked undercover on a federal drug task force, and has spent more than a decade in the U.S. Army. Starting in 2019, he led teams that translated emerging research into capabilities for complex, high-consequence military environments. Alongside his role at Human Voice, Brad is finishing his Ph.D. in Computer Science at Carnegie Mellon University, where his research focuses on audio intelligence, machine learning, and novel sensing techniques.
Garrett Weinberg is a software engineer and user interface designer with over 25 years of experience in speech and voice applications. Most recently he spent 12 years at Apple as a senior interaction designer and design manager for the Siri virtual assistant, responsible for Siri’s voice intelligence layer (among other things). Before Apple, he worked on embedded voice and multimodal systems for vehicles, at companies like Mitsubishi Electric Research Labs and Nuance Communications. Garrett is named as an inventor on 30 patent filings.
Cody Greene, a professional esports athlete turned founder and executive, has built and run operations across AI, manufacturing and media, and has worked on the sale of a major sports franchise. He oversees Human Voice’s operations, pilots and partnerships.
Dr. Bhiksha Raj is a Professor at Carnegie Mellon University’s Language Technologies Institute (LTI). His research spans machine learning, speech processing, computer vision, and time-series analysis, with applications in fields ranging from audio analysis to deep learning and quantum computing. Dr. Raj has contributed to fundamental advancements in robust speech recognition, privacy-preserving machine learning, and neural network architectures, publishing extensively in top conferences such as NeurIPS, ICML, CVPR, and EMNLP. His recent work also explores the intersection of large-scale machine learning models and signal processing, with a focus on real-world challenges.
Maureen Lindsey is an entrepreneur and a builder, always looking for ways to create new value chains and revenue streams, strengthen partnerships, and transform the old to the next. She thrives on innovation, problem solving and collaboration with smart people.
Central graphic based on Caleb’s unique voice.