Speech & natural language publications

We previously proposed the use of MLLR transforms derived from a speech recognition system as speaker features in a speaker verification system. In this paper we report recent improvements to…

We investigate the effect of intentional voice modifications on a state-of-the-art speaker recognition system. The investigation includes data collection, where normal and changed voices are collected from subjects conversing by…

In this paper, we examine the problem of kernel selection for one-versus-all (OVA) classification of multiclass data with support vector machines (SVMs). We focus specifically on the problem of training…

Recent work in speaker recognition has demonstrated the advantage of modeling stylistic features in addition to traditional cepstral features, but to date there has been little study of the relative…

This paper, using case studies of creating speech translation systems between English and languages such as Pashto and Farsi, describes some of the practical issues and the solutions that were…

This paper investigates a scheme for joint segmentation and classification of dialog acts (DAs) of the ICSI Meeting Corpus based on hidden-event language models and a maximum entropy classifier for…

We report on machine learning experiments to distinguish deceptive from nondeceptive speech in the Columbia-SRI-Colorado (CSC) corpus. Specifically, we propose a system combination approach using different models and features for…

In this paper we investigate how portable such features are across domains and languages. We show that even without retraining, English-trained MLP features can provide a significant boost to recognition…

This paper presents the results of initial investigation and experiments into automatic action item detection from transcripts of multi-party human-human meetings.

We investigated automatic action item detection from transcripts of multi-party meetings.

We summarize recent progress in automatic speech-to-text transcription at SRI, ICSI, and the University of Washington. The work encompasses all components of speech modeling found in a state-of-the-art recognition system,…

In this paper, we present a multimodal discourse ontology that serves as a knowledge representation and annotation framework for the discourse understanding component of an artificial personal office assistant.