Speech & natural language
The human voice is a powerful tool. SRI’s speech and language technologies not only allow us to interact more naturally with computing applications—they also provide a wealth of actionable information about our intentions, health and emotional state.
Core technologies and applications
SRI’s Speech Technology and Research (STAR) Laboratory brings together a multidisciplinary mix of engineers, computer scientists and linguists. Together our experts build systems for a wide range of applications including signal processing; data indexing and mining; and computer-aided learning.
Speech production and perception-based features
Prosodic modeling and disfluencies
Speech & audio analytics
Speaker and speaker-state characterization
Audio event detection
Cross-lingual information retrieval
Machine-mediated cross-lingual communication
Natural language understanding
Dialog systems and virtual personal assistants (VPAs)
Error detection and recovery
Semantic and syntactic parsing
Multi-lingual information extraction
Topic and event identification
Open Language Interface for Voice Exploitation (OLIVE)
Novel speech processing technology leverages AI algorithms to enable speech activity detection in high levels of noise and distortion.
Real-time speaker state platform estimates speaker state—such as emotion, sentiment, cognition, health, mental health and communication quality—in a range of end applications.
DynaSpeak® speech recognition engine
Small-footprint, high-accuracy engine incorporates patented techniques that increase recognition performance using speaker adaptation, microphone adaptation, end-of- speech detection, distributed speech recognition and noise robustness.
EduSpeak® speech recognition toolkit
Toolkit specifically designed for language-learning applications and other educational and training software. Works for both adult and child voices, it excels at recognizing native and non-native speakers.
SRI Language Modeling (SRILM)
Toolkit helps build and apply statistical language models for speech recognition, statistical tagging and segmentation, and machine translation. Can be downloaded and used free of charge.
Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option
SRI Authors: Mitchell McLaren, Diego Castán, Aaron Lawson, Mahesh Nandwana
January 1, 2019
I love to work here because SRI International is a place where you find people smarter and nicer than you. They keep me pushing in the right direction and challenging me every day, but with respect and kindness. What else can you ask for?
Advanced Computer Scientist, Information & Computer Science Division
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