Speech & natural language publications

We present an N-best rescoring algorithm that removes the effect of segmentation mismatch. Furthermore, we show that explicit language modeling of hidden linguistic segment boundaries is improved by including turn-boundary…

In this article, we use our interaction model to demonstrate that during multimodal fusion, speech should be a privileged modality, driving the interpretation of a query, and that in certain…

We present a novel approach to hidden Markov model (HMM) state clustering based on the use of broad phone classes and an allophone class entropy measure. Our algorithm allows clustering…

In this paper we show that we can significantly improve HMM- based scores by using average phone segment posterior probabilities. Correlation between machine and human scores went up from r=0.50…

In the context of automatic speaker recognition, we propose a model transformation technique that renders speaker models more robust to acoustic mismatches and to data scarcity by appropriately increasing their…

This paper proposes a probabilstic framework to define and evaluate confidence measures for word recognition. We describe a novel method to combine different knowledge sources and estimate the confidence in…

This paper studies the effects of handset distortion on telephone-based speaker recognition performance. Results on the 1996 NIST Speaker Recognition Evaluation corpus show that using handset-matched background models reduces false…

This paper presents a speech-enabled WWW demonstration based on the Air Travel Information System (ATIS) domain. SRI’s speech recognition technology and natural language understanding are fully integrated in a Java…

We describe the development of the SRI system evaluated in the 1996 DARPA continuous speech recognition (CSR) Hub4 partitioned evaluation (PE). The task for the Hub4 evaluation was to recognition…

In SRI's language modeling experiments for the Hub4 domain, three basic approaches were pursued: interpolating multiple models estimated from Hub4 and non-Hub4 training data, adapting the language model (LM) to…

This paper describes a prototype application which combines speaker identification technology and an agent architecture to provide user-definable monitors for incoming voicemail messages. Through a Web-distributable Java user interface, the…

We present a simple automatic segmenter of transcripts based on N-gram language modeling. We also study the relevance of several word-level features for segmentation performance. Using only word-level information, we…