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
Our workmore +
Aaron Lawson is Assistant Lab Director at SRI’s Speech Technology and Research (STAR) lab. STAR lab brings together a multidisciplinary mix of engineers, computer scientists and linguists. Together their experts build systems for a wide range of applications including signal processing; data indexing and mining; and computer-aided learning. Join us to learn about how STAR…
Speech and Natural language leadership
Novel speech processing technology leverages AI algorithms to enable speech activity detection in high levels of noise and distortion.
In this work, we extend the TBC method, proposing a new similarity metric for selecting training data that results in significant gains over the one proposed in the original work.
Building on multimodal embedding techniques, we show that data augmentation via two distinct approaches improves results: entity linking and cross-domain local similarity scaling.
We argue that to use natural language effectively, we must have both a deep understanding of the subject domain and a general-purpose reasoning capability.
We present a system to perform spectral monitoring of a wide band of 666.5 MHz, located within a range of 6 GHz of Radio Frequency (RF) bandwidth, using state-of-the-art deep learning approaches.
These results indicate a functional interaction between orexin and MCH neurons in vivo that suggests the synergistic involvement of these neuronal populations in the sleep/wakefulness cycle.
To address the challenge of mapping characteristics of individuals’ speech to information about the group, we coded behavioral and learning-related indicators of collaboration at the individual level.
Robust Speaker Recognition from Distant Speech under Real Reverberant Environments Using Speaker Embeddings
This article focuses on speaker recognition using speech acquired using a single distant or far-field microphone in an indoors environment.
In this study, our aim is analyzing the behavior of the speaker recognition systems based on speaker embeddings toward different front-end features, including the standard MFCC, as well as PNCC, and PLP.
Structure-based lead optimization to improve antiviral potency and ADMET properties of phenyl-1H-pyrrole-carboxamide entry inhibitors targeted to HIV-1 gp120
We are continuing our concerted effort to optimize our first lead entry antagonist, NBD-11021, which targets the Phe43 cavity of the HIV-1 envelope glycoprotein gp120, to improve antiviral potency and ADMET properties.