Publication
Subband-Based Speech Recognition in Noisy Conditions: The Full Combination Approach
Publications associées (40)
Support Vector Machines with a Reject Option
We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow’s rule, is defined by two thresholds on posterior probabilities. From simple des ...
2008Using KL-based Acoustic Models in a Large Vocabulary Recognition Task
Hervé Bourlard, Guillermo Aradilla
Posterior probabilities of sub-word units have been shown to be an effective front-end for ASR. However, attempts to model this type of features either do not benefit from modeling context-dependent phonemes, or use an inefficient distribution to estimate ...
IDIAP2008Combining Evidence from a Generative and a Discriminative Model in Phoneme Recognition
Hynek Hermansky, Joel Praveen Pinto
We investigate the use of the log-likelihood of the features obtained from a generative Gaussian mixture model, and the posterior probability of phonemes from a discriminative multilayered perceptron in multi-stream combination for recognition of phonemes. ...
2008Combining Evidence from a Generative and a Discriminative Model in Phoneme Recognition
Hynek Hermansky, Joel Praveen Pinto
We investigate the use of the log-likelihood of the features obtained from a generative Gaussian mixture model, and the posterior probability of phonemes from a discriminative multilayered perceptron in multi-stream combination for recognition of phonemes. ...
IDIAP2008Volterra Series for Analyzing MLP based Phoneme Posterior Probability Estimator
Hynek Hermansky, Joel Praveen Pinto
We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. The identified Volterra kernels reveal the spectro-temporal patterns that are l ...
Idiap2008Comparing Different Word Lattice Rescoring Approaches Towards Keyword Spotting
Hervé Bourlard, Hynek Hermansky, Joel Praveen Pinto
In this paper, we further investigate the large vocabulary continuous speech recognition approach to keyword spotting. Given a speech utterance, recognition is performed to obtain a word lattice. The posterior probability of keyword hypotheses in the latti ...
IDIAP2007On Confusions in a Phoneme Recognizer
Hynek Hermansky, Joel Praveen Pinto
In this paper, we analyze the confusions patterns at three places in the hybrid phoneme recognition system. The confusions are analyzed at the pronunciation, the posterior probability, and the phoneme recognizer levels. The confusions show significant stru ...
2007On Confusions in a Phoneme Recognizer
Hynek Hermansky, Joel Praveen Pinto
In this paper, we analyze the confusions patterns at three places in the hybrid phoneme recognition system. The confusions are analyzed at the pronunciation, the posterior probability, and the phoneme recognizer levels. The confusions show significant stru ...
IDIAP2007The Boolean Solution to the Congested IP Link Location Problem: Theory and Practice
Patrick Thiran, Xuan Hung Nguyen
Like other problems in network tomography or traffic matrix estimation, the location of congested IP links from end-to-end measurements requires solving a system of equations that relate the measurement outcomes with the variables representing the status o ...
2007Identifying unexpected words using in-context and out-of-context phoneme posteriors
Hynek Hermansky, Hamed Ketabdar
The paper proposes and discusses a machine approach for identification of unexpected (zero or low probability) words. The approach is based on use of two parallel recognition channels, one channel employing sensory information from the speech signal togeth ...
IDIAP2006