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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.

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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 recognition

Noise robustness

Speech production and perception-based features

Keyword spotting

Prosodic modeling and disfluencies

Speech & audio analytics

Voice biometrics

Language/accent identification

Speaker and speaker-state characterization

Audio event detection

Speaker diarization

Machine translation

Speech-to-Speech translation

Cross-lingual information retrieval

Machine-mediated cross-lingual communication

Natural language understanding

Human-computer interaction

Dialog systems and virtual personal assistants (VPAs)

Error detection and recovery

Semantic and syntactic parsing

Information extraction

Multi-lingual information extraction

Topic and event identification

Summarization;

Question answering

Our work

more +
  • Nuance Partners with SCIENTIA Puerto Rico
    July 5, 2022

    Nuance Partners with SCIENTIA Puerto Rico

    SRI spin-out Nuance Communications to expand access its Dragon Medical One for the island’s physicians and nurses

  • AI-based speech sentiment analysis technology
    November 22, 2021

    AI-based speech sentiment analysis technology

    Enabling companies to automatically understand the intonation of the human voice.

  • Aaron Lawson talks about the STAR Lab at SRI
    November 16, 2021

    Aaron Lawson talks about the STAR Lab at SRI

    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

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William Mark

President, Information and Computing Sciences

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Dimitra Vergyri

Director, Speech Technology and Research Laboratory (STAR)

Featured researchers

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Dimitra Vergyri

Director, Speech Technology and Research Laboratory (STAR)

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Horacio Franco

Chief Scientist, Speech Technology and Research Laboratory

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Aaron Lawson

Assistant Laboratory Director, Speech Technology and Research Laboratory

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Martin Graciarena

Technical Manager, Speech Technology and Research Laboratory

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Mitchell McLaren

Senior Computer Scientist, Speech Technology and Research Laboratory

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Harry Bratt

Senior Computer Scientist, Speech Technology and Research Laboratory

Platforms

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.

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SenSay

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.

Learn more +

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.

Learn more +

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.

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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.

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Publications

more +
  • Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option

    November 18, 2022

    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.

  • Resilient Data Augmentation Approaches to Multimodal Verification in the News Domain

    October 1, 2021

    Building on multimodal embedding techniques, we show that data augmentation via two distinct approaches improves results: entity linking and cross-domain local similarity scaling.

  • Natural Language Access: When Reasoning Makes Sense

    July 27, 2021

    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.

  • Wideband Spectral Monitoring Using Deep Learning

    July 22, 2020

    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.

  • Dual orexin and MCH neuron-ablated mice display severe sleep attacks and cataplexy

    April 21, 2020

    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.

  • Mapping Individual to Group Level Collaboration Indicators Using Speech Data

    June 1, 2019

    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

    September 1, 2018

    This article focuses on speaker recognition using speech acquired using a single distant or far-field microphone in an indoors environment.

  • Analysis of Complementary Information Sources in the Speaker Embeddings Framework

    September 1, 2018

    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

    June 25, 2018

    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.

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