We present results of an empirical study of the usefulness of different types of features in
selecting extractive summaries of news broadcasts for our Broadcast News Summarization …

Progress in both speech and language processing has spurred efforts to support applications
that rely on spoken rather than written language input. A key challenge in moving from text-…

We present a method for summarizing speech documents without using any type of
transcript/text in a Hidden Markov Model framework. The hidden variables or states in the model …

In this paper, we present approaches used in text summarization, showing how they can be
adapted for speech summarization and where they fall short. Informal style and apparent …

We present a method for summarizing broadcast news that is not affected by word errors in
an automatic speech recognition transcription, using information about the structure of the …

Although phonetic lexicons are critical for many speech applications, the process of building
one for a new language can take a significant amount of time and effort. We present a …

This paper addresses parallel data extraction from the quasi–parallel corpora generated in
a crowd-sourcing project where ordinary people watch tv shows and movies and transcribe/…

We present a methodology for designing and implementing interactive intelligences. The
constructionist design methodology (CDM)--so called because it advocates modular building …

The development of computational data science techniques in natural language processing
(NLP) and machine learning (ML) algorithms to analyze large and complex textual …

The development of computational data science techniques in natural language processing
and machine learning algorithms to analyze large and complex textual information opens …