Results 161 to 170 of about 1,864,117 (195)

Mixup Augmentation for Generalizable Speech Separation

2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP), 2021
Deep learning has advanced the state of the art of single-channel speech separation. However, separation models may overfit the training data and generalization across datasets is still an open problem in real-world conditions with noise. In this paper we address the generalization problem with Mixup as data augmentation approach.
Alex A., Wang L., Gastaldo P., Cavallaro A.   +3 more
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Separation of Speech from Speech Interference Based on EGG

2019
In this paper, a new method based on the Electroglottography (EGG) for solving speech separation problem was proposed. By using the EGG, the mixed speech signals was segmented to silence segment S, unvoiced segment U, and voiced segment V (SUV segmentation) according to the feature of the voiced and unvoiced speech. The V-segment algorithm was based on
Lijiang Chen, Lin Sun, Xia Mao
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Cepstral smoothing of separated signals for underdetermined speech separation

Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010
Musical noise is a typical problem with blind source separation using a time-frequency mask. Recently, the cepstral smoothing of spectral masks (CSM) was proposed. Based on the idea of smoothing in the cepstral domain, this paper proposes the cepstral smoothing of separated signals (CSS) on the assumption that a cepstral representation better reflects ...
Yumi Ansa, Shoko Araki, Shoji Makino, Tomohiro Nakatani, Takeshi Yamada, Atsushi Nakamura, Nobuhiko Kitawaki   +6 more
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Robust speech recognition by integrating speech separation and hypothesis testing

Speech Communication, 2006
Missing-data methods attempt to improve robust speech recognition by distinguishing between reliable and unreliable data in the time-frequency (T-F) domain. Such methods require a binary mask to label speech-dominant T-F regions of a noisy speech signal as reliable and the rest as unreliable.
Soundararajan Srinivasan, DeLiang Wang
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Inharmonic Speech: A Tool for the Study of Speech Perception and Separation

2012
Sounds created by a periodic process have a Fourier representation with harmonic structure – i.e., components at multiples of a fundamental frequency. Harmonic frequency relations are a prominent feature of speech and many other natural sounds. Harmonicity is closely related to the perception of pitch and is believed to provide an important acoustic ...
Josh H. McDermott, Daniel P. W. Ellis, Hideki Kawahara   +2 more
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Convolutive Speech Bases and Their Application to Supervised Speech Separation

IEEE Transactions on Audio, Speech and Language Processing, 2007
In this paper, we present a convolutive basis decomposition method and its application on simultaneous speakers separation from monophonic recordings. The model we propose is a convolutive version of the nonnegative matrix factorization algorithm.
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Speech Separation: Evaluation

2004
Summarizes efforts to launch a debate on unified evaluation standards.
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Speech Detection and Separation

2013
Several methods which are used for speech detection usually fail when SNR is low. The wavelet analysis has properties which can help in separating the speech from other signals. Many works report better detection and separation performance using wavelet analysis than using other techniques.
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A system for speech separation

4th European Conference on Speech Communication and Technology (Eurospeech 1995), 1995
A. Shamsoddini, P. N. Denbigh
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Blind Speech Separation

2007
Part I: Multiple Microphone Blind Speech Separation with ICA 1. Convolutive Blind Source Separation for Speech Signals S.C.Douglas, M.Gupta. 2. Frequency-Domain Blind Source Separation H.Sawada, S.Araki, S.Makino. 3. Blind Source Separation using Space-Time Independent Component Analysis M.Davies, et al. 4.
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