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Práce pojednává o využití support vector machines v detekci řečové aktivity. V první části jsou zkoumány různé druhy příznaků, jejich extrakce a zpracování a je nalezena jejich optimální kombinace, která podává nejlepší výsledky. Druhá část představuje samotný systém pro detekci řečové aktivity a ladění jeho parametrů. Nakonec jsou výsledky porovnány s
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Evaluation of voice activity and voicing detection
Interspeech 2008, 2008This paper describes the ECESS evaluation campaign of voice activity and voicing detection. Standard VAD classifies signal into speech and non-speech, we extend it to VAD+ so that it classifies a signal as a sequence of non-speech, voiced and unvoiced segments.
Kotnik, Bojan +8 more
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On noise robust voice activity detection
Interspeech 2011, 2011In this paper, we show that the performance of voice activity detection algorithms (VAD) can be highlydependent on the type of background noise and we introduce a new VAD algorithm that is based onrelative energy measurements in different frequency bands.
Dekens, Tomas, Verhelst, Werner
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2017
Voice Activity Detection (VAD) provides the information whether an audio signal contains speech or not. Besides speech coding and transmission, there are many other applications in speech and audio processing that benefit from this information, and their performance is crucially dependent on the accuracy and robustness of the applied VAD.
SAINATH TARA N +2 more
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Voice Activity Detection (VAD) provides the information whether an audio signal contains speech or not. Besides speech coding and transmission, there are many other applications in speech and audio processing that benefit from this information, and their performance is crucially dependent on the accuracy and robustness of the applied VAD.
SAINATH TARA N +2 more
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The Journal of the Acoustical Society of America, 1994
Voice activity detector (VAD) for use in an LPC coder in a mobile radio system uses autocorrelation coefficient R 0 , R 1 . . . of the input signal, weighted and combined, to provide a measure M which depends on the power within that part of the spectrum containing no noise, which is thresholded against a variable threshold to provide a speech/no ...
Daniel K. Freeman, Ivan Boyd
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Voice activity detector (VAD) for use in an LPC coder in a mobile radio system uses autocorrelation coefficient R 0 , R 1 . . . of the input signal, weighted and combined, to provide a measure M which depends on the power within that part of the spectrum containing no noise, which is thresholded against a variable threshold to provide a speech/no ...
Daniel K. Freeman, Ivan Boyd
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A new algorithm for voice activity detection
Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03., 2003In this paper, a new VAD (voice activity detection) algorithm based on spectral estimation for the noise suppression system is presented, which divides an input speech signal into specific frequency bands. On the basis of the estimated signal and noise in each sub-band, a signal-to-noise ratio (SNR) which represents a sub-decision signal is calculated ...
Jianqiang Wei +3 more
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Voice Activity Detection Using Neurograms
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018Existing acoustic-signal-based algorithms for Voice Activity Detection (VAD) do not perform well in the presence of noise. In this study, we propose a method to improve VAD accuracy by employing another type of signal representation which is derived from the response of the human Auditory-Nerve (AN) system.
Wissam A. Jassim, Naomi Harte
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Space-time voice activity detection
IEEE Transactions on Consumer Electronics, 2009When speech-based interfaces are used for small handheld devices such as cellular phones and personal digital assistants in mobile environments with unknown noises and surrounding talkers, all signals except the legitimate users voice must be rejected as noise signals by the system.
Hyeopwoo Lee, Dongsuk Yook
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Improving voice activity detection in movies
Interspeech 2015, 2015Voice Activity Detection in movies is a non-trivial and challenging task. The different emotional states of the speakers, as well as the variety of soundscapes and noises contribute to the complexity of the task. In this paper, we propose a set of lightweight features that are specifically designed to perform under such conditions, while at the same ...
Bernhard Lehner +2 more
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