• Skip to primary navigation
  • Skip to main content
SRI logo
  • About
    • Press room
    • Our history
  • Expertise
    • Advanced imaging systems
    • Artificial intelligence
    • Biomedical R&D services
    • Biomedical sciences
    • Computer vision
    • Cyber & formal methods
    • Education and learning
    • Innovation strategy and policy
    • National security
    • Ocean & space
    • Quantum
    • QED-C
    • Robotics, sensors & devices
    • Speech & natural language
    • Video test & measurement
  • Ventures
  • NSIC
  • Careers
  • Contact
  • 日本支社
Search
Close
Artificial intelligence publications September 1, 1995

A Comparative Study of Speaker Adaptation Techniques

Citation

Copy to clipboard


Neumeyer, L., Sankar, A., & Digalakis, V. (1995). A comparative study of speaker adaptation techniques. system, 1, 2.

Abstract

In previous work, we showed how to constrain the estimation of continuous mixture-density hidden Markov models (HMMs) when the amount of adaptation data is small. We used maximum-likelihood (ML) transformation-based approaches and Bayesian techniques to achieve near native performance when testing nonnative speakers of the recognizer language. In this paper, we study various ML-based techniques and compare experimental results on data sets with recordings from nonnative and native speakers of American English. We divide the transformation-based techniques into two groups. In feature-space techniques, we hypothesize an underlying transformation in the feature-space that results in a transformation of the HMM parameters. In model-space techniques, we hypothesize a direct transformation of the HMM parameters. In the experimental section we show how the combination of the best ML and Bayesian adaptation techniques result in significant improvements in recognition accuracy. All the experiments were carried out with SRI’s DECIPHER™ speech recognition system.

↓ Download

Share this

How can we help?

Once you hit send…

We’ll match your inquiry to the person who can best help you.

Expect a response within 48 hours.

Career call to action image

Make your own mark.

Search jobs

Our work

Case studies

Publications

Timeline of innovation

Areas of expertise

Institute

Leadership

Press room

Media inquiries

Compliance

Careers

Job listings

Contact

SRI Ventures

Our locations

Headquarters

333 Ravenswood Ave
Menlo Park, CA 94025 USA

+1 (650) 859-2000

Subscribe to our newsletter


日本支社
SRI International
  • Contact us
  • Privacy Policy
  • Cookies
  • DMCA
  • Copyright © 2022 SRI International