Author: SRI International
-
Nutrition Education Program Nutrition Pathfinders Teaches Children How To Make Healthy Food Choices
-
Rigor, Relevance, And Results: The Quality Of Teacher Assignments And Student Work In New And Conventional High Schools
The Bill & Melinda Gates Foundation’s High School Grants initiative seeks to catalyze the creation of a new kind of American high school—one where every student has a challenging academic program that provides sound preparation for college and for family-wage jobs and the demands of good citizenship.
-
Web-Based Performance Support For Evaluation
The Online Evaluation Resource Library (OERL) is a Web-based electronic performance support system for improving the evaluation of projects funded by theDirectorate for Education and Human Resources (EHR) of the National Science Foundation (NSF).
-
Executive Summary: Evaluation Of The Bill & Melinda Gates Foundation’s High School Grants, 2001-2004
-
Liquid-phase deposition of single-phase alpha-copper-indiumdiselenide,
Based on the first complete CuInSe phase diagram, which was recently established, we propose a new method for making single-phase copper-indium-diselenide (CuInSe2) films for high-specific-power photovoltaic applications: liquid-phase deposition.
-
National Early Intervention Longitudinal Study (NEILS): Family Outcomes at the End of Early Intervention
The report has two primary aims: to describe the outcomes reported by families following their experience with early intervention programs, and to identify a subset of families who were less satisfied with early intervention.
-
The ICSI-SRI-UW Metadata Extraction System
We describe a state-of-the-art system for automatic detection of “metadata” in both broadcast news and spontaneous telephone conversations, developed as part of the DARPA EARS Rich Transcription program.
-
On Using MLP Features in LVCSR
One of the major research thrusts in the speech group at ICSI is to use Multi-Layer Perceptron (MLP) based features in automatic speech recognition (ASR). This paper presents a study of three aspects of this effort.
-
SVM Modeling of “SNERF-Grams” for Speaker Recognition
We describe a new approach to modeling idiosyncratic prosodic behavior for automatic speaker recognition. The approach computes prosodic features by syllable, and models the syllable-feature sequences using support vector machines .
-
Effective Acoustic Modeling for Rate-of-Speech Variation in Large Vocabulary Conversational Speech Recognition
We investigate several variants of speech-rate-dependent acoustic models for large-vocabulary conversational speech recognition, in the framework of combining rate-specific models in decoding to compensate for speech rate variation.
-
From Switchboard to Meetings: Development of the 2004 ICSI-SRI-UW Meeting Recognition System
We describe the ICSI-SRI-UW team’s entry in the Spring 2004 NIST Meeting Recognition Evaluation. The system was derived from SRI’s 5xRT Conversational Telephone Speech (CTS) recognizer by adapting CTS acoustic and language models to the Meeting domain.
-
Using Machine Learning to Cope with Imbalanced Classes in Natural Speech: Evidence from Sentence Boundary and Disfluency Detection
We investigate machine learning techniques for coping with highly skewed class distributions in two spontaneous speech processing tasks. Both tasks, sentence boundary and disfluency detection, provide important structural information for downstream language processing modules.