Performance of Basic Spectral Descriptors and MRMR Algorithm to the Detection of Acoustic Events

Vozarikova, Eva; Lojka, Martin; Juhar, Jozef; Čižmár, Anton

doi:10.1007/978-3-642-30721-8_34

Cited by 6 publications

(3 citation statements)

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“…An exhaustive search for suitable parametric representation of selected set of acoustic events (gunshot and breaking glass) was performed. In our experiments we investigated different parametric representations of the selected acoustic events [14], [15], [16], [17]. Our research was concentrated mainly on the gunshots and breaking glass detection.…”

Section: Figure 3 Acoustic Event Detectionmentioning

confidence: 99%

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Speech Technologies for Advanced Applications in Service Robotics

Ondáš¹,

Juhár²,

Pleva³

et al. 2013

ACTA POLYTECH HUNG

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The multimodal interface for controlling functions of the complex modular robotic system, which can be deployed in difficult conditions as are rescue works, natural disasters, fires, decontamination purposes was designed. Such interface involves several fundamental technologies such as speech recognition, speech synthesis and dialogue management. To enable human operator to cooperate with designed robotic system, the sophisticated architecture was designed and described technologies were implemented. The automatic speech recognition system is introduced, which is based on Hidden Markov models and enables to control functions of the system using a set of voice commands. The text-to-speech system was prepared for producing feedback to the operator and dialogue manager technology was adopted, which makes it possible to perform the information exchange between operator and robotic system. The system proposed is enriched with acoustic event detection system, which consists of a set of five microphones integrated on the robotic vehicle, the post-processing unit and detection unit.

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Section: Figure 3 Acoustic Event Detectionmentioning

confidence: 99%

“…Our research was concentrated mainly on the gunshots and breaking glass detection. Many tests were performed using various feature extraction algorithms and also with using of mutual information-based feature selection [16].…”

Section: Figure 3 Acoustic Event Detectionmentioning

confidence: 99%

Speech Technologies for Advanced Applications in Service Robotics

Ondáš¹,

Juhár²,

Pleva³

et al. 2013

ACTA POLYTECH HUNG

View full text Add to dashboard Cite

show abstract

“…The MRMR algorithm performs well on microarray gene data [21] and abnormal acoustic events occurred in public places, such that gun shot, explosions and breaking glass [22], as well.…”

mentioning

confidence: 99%

The SVM Binary Tree Classification Using MRMR and F-Score Feature Selection Algorithms

Vavrek

Juhár

Čižmár

2014

AEI

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The discrimination between various types of speech and non-speech signals in audio data stream is the fundamental step for further indexing and retrieving. This paper considers some of the basic problems in audio content classification which is the key component in automatic audio retrieval system. It illustrates a potential use of statistical learning algorithm called support vector machine (SVM) for broadcast news (BN) audio classification task. The overall classification architecture uses binary tree SVM (BT-SVM) decision scheme in combination with well known audio features such as, MFCCs and low level MPEG-7 audio descriptors. The important step in creating such classification system is to define the optimal features for each binary SVM classifier. There exist various feature selection algorithms that help to create such feature set. Therefore we decided to implement F-score and Minimum Redundancy Maximum Relevance (MRMR) feature selection algorithms, as an effective search algorithms used in many pattern recognition tasks.

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