András Bánhalmi

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For One-Class Classification problems several methods have been proposed in the literature. These methods all have the common feature that the decision boundary is learnt by just using a set of the positive examples. Here we propose a method that extends the training set with a counter-example set, which is generated directly using the set of positive(More)
This paper proposes a pitch estimation algorithm that is based on optimal harmonic model fitting. The algorithm operates directly on the time-domain signal and has a relatively simple mathematical background. To increase its efficiency and accuracy, the algorithm is applied in combination with an autocorrelation-based initialization phase. For testing(More)
This paper reviews the current state of a Hungarian project that seeks to create a speech recognition system for the dictation of thyroid gland medical reports. We present the MRBA speech corpus that was collected to support the training of Hungarian LVCSR systems. Besides the speech data, a huge set of medical reports was also collected to help the(More)
Our aim is to implement a plant identification application that can run on smartphones, and this shared task includes it. After the plant identification task of 2013 we concluded that the most frequent trees (e. g. in Hungary) can be identified well by a leaf, when there is a white paper background behind it at the time of photographing. This is why we want(More)
Prevention and rehabilitation efficiency can greatly benefit from the application of intelligent, 24 hour tele-diagnostics and tele-care information systems. Tele-monitoring also supports a new level of medical supervision over the patient's lifestyle. In this paper we briefly present the architecture and development phase results of the Alpha remote(More)
This paper examines the susceptibility of a dictation system to various types of mismatches between the training and testing conditions. With these experiments we intend to find the best training configuration for the system and also to evaluate the efficiency of the speaker adaptation algorithm we use. The paper first presents the components of the(More)
Several pitch estimation algorithms have been proposed over the decades, but they have tended to become more and more complex and cumbersome, some of them requiring much more computational power than a real-time application can afford. Rather than have one sophisticated algorithm, here we propose to combine the output of several conventional and relatively(More)
In the past few years numerous techniques have been proposed to improve the efficiency of basic adaptation methods like MLLR and MAP. These adaptation methods have a common aim, which is to increase the likelihood of the phoneme models for a particular speaker. During their operation, these speaker adaptation methods need precise phonetic segmentation(More)