EPFL lab session 2/2: Introduction to Hidden Markov Models
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There is magic (or is it witchcraft?) in a speech recognizer that transcribes continuous radio speech into text with a word accuracy of even not more than 50%. The extreme difficulty of this task, tough, is usually not perceived by the general public. This ...
Most state-of-the-art automatic speech recognition (ASR) systems deal with noise in the environment by extracting noise robust features which are subsequently modelled by a Hidden Markov Model (HMM). A limitation of this feature-based approach is that the ...
This paper presents an approach for the segmentation of broadcast news into stories. The main novelty of this work is that the segmentation process does not take into account the content of the news, i.e. what is said, but rather the structure of the socia ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
This paper presents a method for monitoring activities at a ticket vending machine in a video-surveillance context. Rather than relying on the output of a tracking module, which is prone to errors, the events are direclty recognized from image measurements ...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often unrealistic assumptions on the conditional independence of observations given ...
Contextual information is important for sequence modeling. Hidden Markov Models (HMMs) and extensions, which have been widely used for sequence modeling, make simplifying, often unrealistic assumptions on the conditional independence of observations given ...
In a previous paper on speech recognition, we showed that templates can better capture the dynamics of speech signal compared to parametric models such as hidden Markov models. The key point in template matching approaches is finding the most similar templ ...
This paper presents an approach for the segmentation of broadcast news into stories. The main novelty of this work is that the segmentation process does not take into account the content of the news, i.e. what is said, but rather the structure of the socia ...
In a previous paper on speech recognition, we showed that templates can better capture the dynamics of speech signal compared to parametric models such as hidden Markov models. The key point in template matching approaches is finding the most similar templ ...
