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ICIP
2000
IEEE
16 years 5 months ago
Normalized Training for HMM-Based Visual Speech Recognition
This paper presents an approach to estimating the parameters of continuous density HMMs for visual speech recognition. One of the key issues of image-based visual speech recogniti...
Yoshihiko Nankaku, Keiichi Tokuda, Tadashi Kitamur...
145
Voted
ESANN
1998
15 years 5 months ago
Speech recognition with a new hybrid architecture combining neural networks and continuous HMM
Abstract. In this paper, we focus on a novel NN/HMM architecture for continuous speech recognition. The architecture incorporates a neural feature extraction to gain more discrimin...
Daniel Willett, Gerhard Rigoll
118
Voted
NAACL
2007
15 years 5 months ago
Virtual Evidence for Training Speech Recognizers Using Partially Labeled Data
Collecting supervised training data for automatic speech recognition (ASR) systems is both time consuming and expensive. In this paper we use the notion of virtual evidence in a g...
Amarnag Subramanya, Jeff A. Bilmes
107
Voted
ICMCS
2005
IEEE
147views Multimedia» more  ICMCS 2005»
15 years 9 months ago
Comparing Feature Sets for Acted and Spontaneous Speech in View of Automatic Emotion Recognition
We present a data-mining experiment on feature selection for automatic emotion recognition. Starting from more than 1000 features derived from pitch, energy and MFCC time series, ...
Thurid Vogt, Elisabeth André
117
Voted
ICANN
2005
Springer
15 years 9 months ago
Classifying Unprompted Speech by Retraining LSTM Nets
Abstract. We apply Long Short-Term Memory (LSTM) recurrent neural networks to a large corpus of unprompted speech- the German part of the VERBMOBIL corpus. Training first on a fra...
Nicole Beringer, Alex Graves, Florian Schiel, J&uu...