Publications

We quantify how the telephone channel and regional dialect influence formant estimates extracted from Wavesurfer in spontaneous conversational speech from over 3,600 native American English speakers. To the best of our knowledge, this is the largest scale study on this topic. We found that F1 estimates are higher in cellular...

The idea of a mechanical process for converting one human language into another can be traced to a letter written by René Descartes in 1629, and after nearly 400 years, this vision has not been fully realized. Machine translation (MT) using digital computers has been a grand challenge for computer...

Advocate is a set of communications application programming interfaces and service wrappers that serve as a framework for creating complex and scalable real-time software applications from component processing algorithms. Advocate can be used for a variety of distributed processing applications, but was initially designed to use existing speech processing and...

Advocate is a lightweight and easy-to-use computing architecture that supports real-time, voice-oriented computing. It is designed to allow the combination of multiple speech and language processing components to create cohesive distributed applications. It is scalable, supporting local processing of all NLP/speech components when sufficient processing resources are available to one...

There has long been a desire to be able to identify a person on the basis of his or her voice. For many years, judges, lawyers, detectives, and law enforcement agencies have wanted to use forensic voice authentication to investigate a suspect or to confirm a judgment of guilt or...

This paper describes the construction of ASR and MT systems for translation of speech from Urdu into English. As both Urdu pronunciation lexicons and Urdu-English bitexts are sparse, we employ several techniques that make use of semi-supervised annotation to improve ASR and MT training. Specifically, we describe 1) the construction...

This paper describes advances in the use of confusion networks as interface between automatic speech recognition and machine translation. In particular, it presents a decoding algorithm for confusion networks which results as an extension of a state-of-the-art phrase-based text translation decoder. The confusion network decoder significantly improves both in efficiency...

In this paper, we introduce a dialect recognition method that makes use of phonetic models adapted per dialect without phonetically labeled data. We show that this method can be implemented efficiently within an existing PRLM system. We compare the performance of this system with other state-of-the-art dialect recognition methods (both...

This paper presents a description of the MIT Lincoln Laboratory language recognition system submitted to the NIST 2007 Language Recognition Evaluation. This system consists of a fusion of four core recognizers, two based on tokenization and two based on spectral similarity. Results for NIST?s 14-language detection task are presented for...

This paper describes two experimental protocols for direct comparison on human and machine phonetic discrimination performance in continuous speech. These protocols attempt to isolate phonetic discrimination while controlling for language and segmentation biases. Results of two human experiments are described including comparisons with automatic phonetic recognition baselines. Our experiments suggest...