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(PDF) Robust speech / music classification in audio …
https://www.researchgate.net/publication/221479493_Robust_speech_music_classification_in_audio_documents
PDF | On Jan 1, 2002, Julien Pinquier and others published Robust speech / music classification in audio documents. | Find, read and cite all the research you need …
(PDF) Robust speech / music classification in audio ...
https://www.academia.edu/4330775/Robust_speech_music_classification_in_audio_documents
ROBUST SPEECH / MUSIC CLASSIFICATION IN AUDIO DOCUMENTS ´ Julien PINQUIER, Jean-Luc ROUAS and R´egine ANDRE-OBRECHT Institut de Recherche en Informatique de Toulouse, UMR 5505 CNRS INP UPS 118, route de Narbonne, 31062 Toulouse cedex 04, FRANCE pinquier, rouas, obrecht @irit.fr ABSTRACT used to separate voiced speech from noisy sounds [4], [5] This …
Robust speech / music classification in audio documents
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.653.4176
audio document robust speech music classification music segmentation key word entropy modulation tv movie soundtrack correct identification rate original feature topic retrieval collected sample novel approach development corpus first experiment modula-tion energy stationary segment duration
Robust speech / music classification in audio documents
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.653.821
audio document robust speech music classification music segmentation key word employed algo-rithm tv movie soundtrack correct identification rate original feature topic retrieval collected sample segmental pa-rameters modulation entropy novel approach development corpus hz mod-ulation energy first experiment
CiteSeerX — Robust speech / music classification in …
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.652.6868
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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.
(PDF) Speech and music classification in audio …
https://www.academia.edu/4330778/Speech_and_music_classification_in_audio_documents
The precision of the speech classification (accuracy) (2) is The Speech model is trained from signal containing audible excellent: 99.5%. speech (i.e. pure or mixed with music when it does not For the music, the rate of delays lower than 20 cs is damage too much speech or mixed with noise such as 91 % and the accuracy is 93 %.
(PDF) Speech and music classification in audio documents
https://www.researchgate.net/publication/228548255_Speech_and_music_classification_in_audio_documents
Speech/music classification is an integral part of various consumer electronics applications such as audio codecs, multimedia document indexing, and automatic speech recognition.
Robust speech / music classification in audio documents …
https://core.ac.uk/display/102772473
Robust speech / music classification in audio documents . By Julien Pinquier, Christine Sénac and Régine André-obrecht. Abstract. 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 ...
Robust speech / music classification in audio documents …
https://core.ac.uk/display/102789698
Robust speech / music classification in audio documents . ... of these features is evaluated in a first experiment based on a development corpus composed of collected samples of speech and music. Another corpus is employed to verify the robustness of the employed algo-rithm. ... MOTIVATIONS To describe and index an audio document, key words or ...
Speech/Music Classification Using Features From …
https://ieeexplore.ieee.org/document/9089263/
Spectrograms of speech and music contain distinct striation patterns. Traditional features represent various properties of the audio signal but do not necessarily capture such patterns. This work proposes to model such spectrogram patterns using a novel Spectral Peak Tracking (SPT) approach. Two novel time-frequency features for speech vs. music …
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