Speech & natural language publications

In this paper, we present our approach for using information extraction annotations to augment document retrieval for distillation. We take advantage of the fact that some of the distillation queries…

We investigate the application of the co-training learning algorithm on the sentence boundary classification problem by using lexical and prosodic information. Co-training is a semisupervised machine learning algorithm that uses…

We present an application of unsupervised language model (LM) adaptation to meeting recognition, in a scenario where sequences of multiparty meetings on related topics are to be recognized, but no…

This paper uses a state-of-the-art Mandarin recognition system as a platform to study the interaction of three techniques. Experiments in the broadcast news and broadcast conversation domains show that the…

We present an approach that integrates multiple components and models for improved speaker identification in spontaneous Arabic speech in adverse acoustic conditions.

We present specific techniques and results from SRI’s NIST speaker recognition evaluation system.

This paper explores the important question of finding a good kernel for a system that models syllable-based prosodic features using support vector machines (SVMs). We introduce two new methods for…

In this paper, we present a statistical sentence extraction approach for distillation. Basically, we frame this task as a classification problem, where each candidate sentence in documents is classified as…

We compare two recently proposed techniques, within class covariance normalization (WCCN) [1] and nuisance attribute projection (NAP) [2], for intersession variability compensation in speaker verification.

We analyze subword-based language models (LMs) in large-vocabulary continuous speech recognition across four “morphologically rich” languages: Finnish, Estonian, Turkish, and Egyptian Colloquial Arabic.

We describe the development of the ICSI-SRI speech recognition system for the NIST Spring 2006 Meeting Rich Transcription (RT-06S) evaluation, highlighting improvements, including the delay-and-sum algorithm, the nearfield segmenter, language…