Results 221 to 230 of about 45,066 (261)

Audio segmentation based on multi-scale audio classification

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004
Content-based audio segmentation plays an important role in multimedia applications. In order to segment accurately and on-line, most conventional algorithms are based on small-scale feature classification and always result in a high false alarm rate.
Yibin Zhang, Jie Zhou 0001
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Genre classification of compressed audio data

2008 IEEE 10th Workshop on Multimedia Signal Processing, 2008
This paper deals with the musical genre classification problem, starting from a set of features extracted directly from MPEG-1 layer III compressed audio data. The automatic classification of compressed audio signals into a short hierarchy of musical genres is explored. More specifically, three feature sets for representing timbre, rhythmic content and
RIZZI, Antonello, BUCCINO, NICOLA MAURIZIO, PANELLA, Massimo, UNCINI, Aurelio   +3 more
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Classification of audios containing speech and music

2012 20th Signal Processing and Communications Applications Conference (SIU), 2012
We propose an automated technique that uses perceptual and non-perceptual audio quality measures for discrimination of speech and music signals with high accuracy. Deployed audio quality measures used for characterization of audio are obtained via de-noising of the original audio. The underlying idea of the approach is that de-noising operation affects
Uzun, Erkam, Sencar, Hüsrev Taha
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Feature Analysis for Audio Classification

2014
In this work we analyze and implement several audio features. We emphasize our analysis on the ZCR feature and propose a modification making it more robust when signals are near zero. They are all used to discriminate the following audio classes: music, speech, environmental sound. An SVM classifier is used as a classification tool, which has proven to
Gaston Bengolea, Daniel G. Acevedo, Martin Rais, Marta Mejail   +3 more
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Text classification: A preferred tool for audio file classification

2008 IEEE/ACS International Conference on Computer Systems and Applications, 2008
This paper presents a general outline related to the numerical classification generalization applied to sound documents. The approach put forward combines concepts pertaining to natural language processing and frequency analysis. The raw data of the audio documents are converted into strings of alphanumerical characters that are well suited to ...
Louis Rompre, Ismaïl Biskri, François Meunier   +2 more
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Audio Classification with Thermodynamic Criteria

2014 IEEE International Conference on Cloud Engineering, 2014
Detecting sound events in audio recordings is a challenging problem. A detector must be trained for each sound to be classified. However, the recordings of the examples used to train the detector rarely match the conditions found in the test audio to be classified.
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Speech and music classification in audio documents

IEEE International Conference on Acoustics Speech and Signal Processing, 2002
To index efficiently the soundtrack of multimedia documents, it is necessary to extract elementary and homogeneous acoustic segments. In this paper, we explore such a prior partitioning which consists in detect the two basic components, which are speech and music components.
Julien Pinquier, Christine Sénac
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A robust audio classification and segmentation method

Proceedings of the ninth ACM international conference on Multimedia, 2001
In this paper, we present a robust algorithm for audio classification that is capable of segmenting and classifying an audio stream into speech, music, environment sound and silence. Audio classification is processed in two steps, which makes it suitable for different applications.
Lie Lu, Hao Jiang 0007, HongJiang Zhang
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An Unsupervised Audio Segmentation and Classification Approach

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007
This paper presents an unsupervised audio segmentation and classification approach. First, the multiple change-point segmentation is adopted, and a new feature named Mel-ICA is introduced to improve it. An audio type "uncertain" is proposed to represent mixed type.
Wenjuan Pan, Yong Yao, Zhijing Liu
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Audio signal classification with temporal envelopes

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
The conventional approach to audio processing, based on the short-time power spectrum model, is not adequate when it comes to general audio signals. We propose an approach, justified by studies from psycho-acoustics and neuroimaging, which uses the magnitude and frequency envelope of the audio signal in the from of AM-FM modulations to build an ARMA ...
M. Umair Bin Altaf, Biing-Hwang Juang
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