Article Submitted to Computer Speech and Language (2007)
Lidia Mangu, Eric Brill, Andreas Stolcke
Finding consensus in speech recognition: word error minimization and other applications of confusion networks
Error corrective mechanisms for speech recognition (2001)
Lidia Mangu, Mukund Padmanabhan
In the standard MAP approach to speech recognition, the goal is to find the word sequence with the highest posterior probability given the acoustic observation. Recently, a number of alternate...
Advances in speech transcriptions at IBM under the DARPA EARS program (2000)
Stanley Chen, Brian Kingsbury, Lidia Mangu, Daniel Povey, George Saon, Hagen Soltau, ...
Abstract—This paper describes the technical and system building advances made in IBM’s speech recognition technology over the course of the DARPA Effective Affordable Reusable Speechto-Text...
Lattice Compression in the Consensual Post-Processing Framework (1999)
Word Lattices are used by most speech recognizers as a compact representation of a set of alternative hypotheses. In large-vocabulary, multi-pass recognition systems it is important to generate word...
Hierarchical Topic-sensitive Language Models for Automatic Speech Recognition (1999)
Language modeling is the attempt to identify regularities in natural language and capture them in a statistical model. Language models are crucial ingredients in automatic speech recognition where a...
Beyond n-grams: Can linguistic sophistication improve language modeling (1998)
Eric Brill, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Beyond n-grams: Can linguistic sophistication improve language modeling (1998)
Eric Brill, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Beyond N-Grams: Can Linguistic Sophistication Improve Language Modeling? (1998)
Eric Brill Radu, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Beyond N-Grams: Can Linguistic Sophistication Improve Language Modeling? (1998)
Eric Brill, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Beyond N-Grams: Can Linguistic Sophistication Improve Language Modeling? (1998)
Eric Brill, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Beyond n-grams: Can linguistic sophistication improve language modeling (1998)
Eric Brill, Radu Florian, John C. Henderson, Lidia Mangu
It seems obvious that a successful model of natural language would incorporate a great deal of both linguistic and world knowledge. Interestingly, state of the art language models for speech...
Automatic Rule Acquisition for Spelling Correction (1997)
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledge is captured in a...
Dependency Language Modeling (1997)
Andreas Stolcke, Ciprian Chelba, David Engle, Victor Jimenez, Lidia Mangu, Harry Printz, ...
This report summarizes the work of the Dependency Language Modeling group at the 1996 Summer Speech Workshop at the Center for Language and Speech Processing at Johns Hopkins University (WS96). We...
Structure And Performance Of A Dependency Language Model (1997)
Ciprian Chelba, David Engle, Frederick Jelinek, Victor Jimenez, Sanjeev Khudanpur, Lidia Mangu, ...
We present a maximum entropy language model that incorporates both syntax and semantics via a dependency grammar. Such a grammar expresses the relations between words by a directed graph. Because the...
Structure and Performance of a Dependency Language Model (1997)
Ciprian Chelba, David Engle, Frederick Jelinek, Victor Jimenez, Sanjeev Khudanpur, Lidia Mangu, ...
We present a maximum entropy language model that incorporates both syntax and semantics via a dependency grammar. Such a grammar expresses the relations between words by a directed graph. Because the...
Finding Consensus Among Words: Lattice-Based Word Error Minimization
Lidia Mangu, Eric Brill, Andreas Stolcke
We describe a new algorithm for finding the hypothesis in a recognition lattice that is expected to minimize the word error rate (WER). Our approach thus overcomes the mismatch between the word-based...