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Computational intelligence in processing of speech acoustics: a survey
Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …
presents a comprehensive survey on the speech recognition techniques for non-Indian and …
Framewise speech-nonspeech classification by neural networks for voice activity detection with statistical noise suppression
Y Obuchi - 2016 IEEE International Conference on Acoustics …, 2016 - ieeexplore.ieee.org
A new voice activity detection (VAD) algorithm is proposed. The proposed algorithm is the
combination of augmented statistical noise suppression (ASNS) and convolutional neural …
combination of augmented statistical noise suppression (ASNS) and convolutional neural …
Phase aware deep neural network for noise robust voice activity detection
Phase information is ignored for almost all voice activity detection (VAD). To exploit full
information in the original signal, this paper proposes a deep neural network (DNN) using …
information in the original signal, this paper proposes a deep neural network (DNN) using …
Noise robust voice activity detection using joint phase and magnitude based feature enhancement
Recently, deep neural network (DNN)-based feature enhancement has been proposed for
many speech applications. DNN-enhanced features have achieved higher performance …
many speech applications. DNN-enhanced features have achieved higher performance …
Robust voice activity detection based on concept of modulation transfer function in noisy reverberant environments
Voice activity detection (VAD) is used to detect speech and non-speech periods from
observed speech signals. It is an important front-end technique for many speech technology …
observed speech signals. It is an important front-end technique for many speech technology …
[PDF][PDF] CENSREC-4: development of evaluation framework for distant-talking speech recognition under reverberant environments.
In this paper, we newly introduce a collection of databases and evaluation tools called
CENSREC-4, which is an evaluation framework for distant-talking speech under hands-free …
CENSREC-4, which is an evaluation framework for distant-talking speech under hands-free …
DNN-based voice activity detection using auxiliary speech models in noisy environments
Voice activity detection (VAD) is essential for automatic speech recognition (ASR) in noisy
environments. Deep neural network (DNN)-based VAD is more powerful than previous …
environments. Deep neural network (DNN)-based VAD is more powerful than previous …
Noise-robust voice conversion based on sparse spectral map** using non-negative matrix factorization
This paper presents a voice conversion (VC) technique for noisy environments based on a
sparse representation of speech. Sparse representation-based VC using Non-negative …
sparse representation of speech. Sparse representation-based VC using Non-negative …
Close/distant talker discrimination based on kurtosis of linear prediction residual signals
Desired/undesired speech discrimination is as important as speech/non-speech
discrimination to achieve useful applications such as speech interfaces and …
discrimination to achieve useful applications such as speech interfaces and …
Multimodal voice conversion using non-negative matrix factorization in noisy environments
This paper presents a multimodal voice conversion (VC) method for noisy environments. In
our previous NMF-based VC method, source exemplars and target exemplars are extracted …
our previous NMF-based VC method, source exemplars and target exemplars are extracted …