Publications

Automatic language recognition from speech consists of algorithms and techniques that model and classify the language being spoken. Current state-of-the-art language recognition systems fall into two broad categories: spectral- and token-sequence-based approaches. In this chapter, we describe algorithms for extracting features and models representing these types of language cues and...

We describe the construction and use of a laboratory facility for testing the performance of speech-to-speech translation devices. Approximately 1500 English phrases from various military domains were recorded as spoken by each of 30 male and 12 female English speakers with variation in speaker accent, for a total of approximately...

In this paper we describe an efficient implementation of a graph search algorithm for phrase-based statistical machine translation. Our goal was to create a decoder that could be used for both our research system and a real-time speech-to-speech machine translation demonstration system. The search algorithm is based on a Viterbi...

The MIT-LL/AFRL MT system is a statistical phrase-based translation system that implements many modern SMT training and decoding techniques. Our system was designed with the long-term goal of dealing with corrupted ASR input and limited amounts of training data for speech-to-speech MT applications. This paper will discuss the architecture of...

This paper describes the SMT we built during the 2006 JHU Summer Workshop for the IWSLT 2006 evaluation. Our effort focuses on two parts of the speech translation problem: 1) efficient decoding of word lattices and 2) novel applications of factored translation models to IWSLT-specific problems. In this paper, we...

We present observations from three exercises designed to map the effective listening and speaking skills of an operator of a speech-to-speech translation system (S2S) to the Interagency Language Roundtable (ILR) scale. Such a mapping is nontrivial, but will be useful for government and military decision makers in managing expectations of...

This paper presents a description of the MIT Lincoln Laboratory submissions to the 2005 NIST Language Recognition Evaluation (LRE05). As was true in 2003, the 2005 submissions were combinations of core cepstral and phonotactic recognizers whose outputs were fused to generate final scores. For the 2005 evaluation, Lincoln Laboratory had...

In this paper we describe experiments conducted during the development of a lattice-based PPRLM language identification system as part of the NIST 2005 language recognition evaluation campaign. In experiments following LRE05 the PPRLM-lattice sub-system presented here achieved a 30s/primary condition EER of 4.87%, making it the single best performing recognizer...

The MITLL/AFRL MT system is a statistical phrase-based translation system that implements many modern SMT training and decoding techniques. Our system was designed with the long term goal of dealing with corrupted ASR input for Speech-to-Speech MT applications. This paper will discuss the architecture of the MITLL/AFRL MT system, and...

We report on results of two experiments designed to compare subjects' ability to extract information from audio recordings of conversational telephone speech (CTS) with their ability to extract information from text transcripts of these conversations, with and without the ability to hear the audio recordings. Although progress in machine processing...