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This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic ...
This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distanc ...
This paper proposes a discriminative approach to template-based keyword detection. We introduce a method to learn the distance used to compare acoustic frames, a crucial element for template matching approaches. The proposed algorithm estimates the distanc ...
This paper proposes a new approach for keyword spotting, which is not based on HMMs. The proposed method employs a new discriminative learning procedure, in which the learning phase aims at maximizing the area under the ROC curve, as this quantity is the m ...
In this paper we investigate the detection and recognition of sequences of numbers in spoken utterances. This is done in two steps: first, the entire utterance is decoded assuming that only numbers were spoken. In the second step, non-number segments (garb ...
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. ...
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. ...
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 ...
In this paper we investigate the detection and recognition of sequences of numbers in spoken utterances. This is done in two steps: first, the entire utterance is decoded assuming that only numbers were spoken. In the second step, non-number segments (garb ...
