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A hierarchical framework approach for voice activity ...
[13] X. Bao and J. Zhu, "A novel voice activity detection based on phoneme recognition using statistical model," Journal on Audio, Speech, and Music Processing, vol. 2012, article 1, 2012. [14] M. H. Moattar and M. M. Homayounpour, "A weighted feature voting approach for robust and real-time voice activity detection," ETRI Journal, vol. 33, no ......
arXiv:2008.02487v1 [eess.AS] 6 Aug 2020
signals that are framed using a 25 ms analysis window with a 10 ms shift. Voice activity detection is employed to discard non-speech frames. Then, prior PLDA scoring, x-vectors are centered, reduced in terms of dimensionality by means of linear discriminant analysis and length-normalized. 5.2. Test Database
Publications - Tetsuji Ogawa
Naohiro Tawara, Tetsuji Ogawa, Tetsunori Kobayashi, ``A comparative study of spectral clustering for i-vector-based speaker clustering under noisy conditions,’’ Proc. ICASSP2015, pp.2041-2045, April 2015. [doi: 10.1109/ICASSP.2015.7178329]
Improving Hands-Free Speech Recognition in a Car Through ...
For voice activity detection, the relative position of the speaker to the microphone array is estimated based on the multichannel cross correlation coefficient (MCCC) [4]. At the same time, the visible mouth region is identified by the face tracking system. After these localization steps, the sig-nal of the desired speaker is extracted with a ...
Techniques for Noise Robustness in Automatic Speech ...
Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems.
Vijayachandran mariappan - Freelancer, working in Machine ...
Voice activity detection (VAD) has become an integral part of many Wireless Cellular and Personal Communications Systems. In this paper, a pitch based VAD for rough noisy environments is presented ...
An Improved Speech Segmentation and Clustering Algorithm ...
This paper studies the segmentation and clustering of speaker speech. In order to improve the accuracy of speech endpoint detection, the traditional double-threshold short-time average zero-crossing rate is replaced by a better spectrum centroid feature, and the local maxima of the statistical feature sequence histogram are used to select the threshold, and a new speech endpoint detection ...
Elias Nemer - Los Angeles Metropolitan Area | Professional ...
A dual-microphone subband-based Voice Activity Detector using higher-order cumulants ... basis for speech detection. Their immunity to Gaussian noise makes them particularly useful in algorithms ...
Peyman Tehrani - Research Assistant - UC Irvine | LinkedIn
4- Implementation of a image segmentation method using Gaussian mixture model. Auto-correlation based voice activity detection ... between a speech mixed with background noise and a background ...
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