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This document describes a neural method for clustering words and its use in language modeling for speech recognizers. The method is based on clustering the words which appear on similar local context and estimating the parameters needed for language modeli ...
The challenge of automatic speech recognition (ASR) increases when speaker variability is encountered. Being able to automatically use different acoustic models according to speaker type might help to increase the robustness of ASR. We present a system tha ...
Articulatory representations are expected to bring better speech recognition results. This requires to estimate the parameters of a speech production model from the speech sound, problem known as acoustico-articulatory inversion. Known methods to solve thi ...
In this report, we discuss the initial issues addressed in a research project aiming at the development of an advanced natural speech recognition system for the automatic processing of telephone directory requests. This multi-faceted project involves (1) t ...
We describe a method for tracking tongue, lips, and throat in X-ray films showing the side-view of the vocal tract. The technique uses specialized histogram normalization techniques and a new tracking method that is robust against occlusion, noise, and spo ...
The paper presents the European ACTS project “M2VTS” which stands for Multi Modal Verification for Teleservices and Security Applications. The primary goal of this project is to address the issue of secured access to local and centralised services in a mul ...
Multi-band ASR was largely inspired by the extremely high level of redundancy in the spectral signal representation which can be inferred from Fletcher's product-of-errors rule for human speech perception. Indeed, the main aim of the multi-band approach is ...
Current technology for automatic speech recognition (ASR) uses hidden Markov models (HMMs) that recognize spoken speech using the acoustic signal. However, no use is made of the causes of the acoustic signal: the articulators. We present here a dynamic Bay ...
This paper proposes a method for recovering the articulatory parameters of a factor-based vocal tract shape model from the speech waveform. This is realized by analytically relating the shape model to a Linear Prediction lattice filter. Results pertaining ...
Current technology for automatic speech recognition (ASR) uses hidden Markov models (HMMs) that recognize spoken speech using the acoustic signal. However, no use is made of the causes of the acoustic signal: the articulators. We present here a dynamic Bay ...
