Speaker Re-identification with Speaker Dependent Speech Enhancement [PDF]
, 2020 While the use of deep neural networks has significantly boosted speaker recognition performance, it is still challenging to separate speakers in poor acoustic environments.
Hain, Thomas, Huang, Qiang, Shi, Yanpei
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Research Status and Prospect of Transformer in Speech Recognition
Jisuanji kexue yu tansuo, 2021 As a new deep learning algorithm framework, Transformer has attracted more and more researchers?? attention and has become a current research hotspot. Inspired by humans focusing on important things only, the self-attention mechanism in the Transformer ...
ZHANG Xiaoxu, MA Zhiqiang, LIU Zhiqiang, ZHU Fangyuan, WANG Chunyu
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Audio-visual speech recognition with background music using single-channel source separation [PDF]
, 2012 In this paper, we consider audio-visual speech recognition with background music. The proposed algorithm is an integration of audio-visual speech recognition and single channel source separation (SCSS). We apply the proposed algorithm to recognize spoken
Erdogan, Hakan +4 more
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Recognizing Voice Over IP: A Robust Front-End for Speech Recognition on the World Wide Web [PDF]
, 2001 The Internet Protocol (IP) environment poses two relevant sources of distortion to the speech recognition problem: lossy speech coding and packet loss. In this paper, we propose a new front-end for speech recognition over IP networks.
Díaz de María, Fernando +2 more
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Emotional Interactive Simulation System of English Speech Recognition in Virtual Context
Complexity, 2020 With the development of virtual scenes, the degree of simulation and functions of virtual reality have been very complete, providing a new platform and perspective for teaching design.
Dan Li
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Selection of acoustic modeling unit for Tibetan speech recognition based on deep learning [PDF]
MATEC Web of Conferences, 2021 The selection of the speech recognition modeling unit is the primary problem of acoustic modeling in speech recognition, and different acoustic modeling units will directly affect the overall performance of speech recognition.
Gong Baojia +4 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2021 The performance of speech recognition systems trained with neutral utterances degrades significantly when these systems are tested with emotional speech. Since everybody can speak emotionally in the real-world environment, it is necessary to take account
Masoud Geravanchizadeh +2 more
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Effect of Time-domain Windowing on Isolated Speech Recognition System Performance [PDF]
International Journal of Electronics and Telecommunications, 2022 Speech recognition system extract the textual data from the speech signal. The research in speech recognition domain is challenging due to the large variabilities involved with the speech signal.
Ananthakrishna Thalengala +2 more
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A novel privacy-preserving speech recognition framework using bidirectional LSTM
Journal of Cloud Computing: Advances, Systems and Applications, 2020 Utilizing speech as the transmission medium in Internet of things (IoTs) is an effective way to reduce latency while improving the efficiency of human-machine interaction. In the field of speech recognition, Recurrent Neural Network (RNN) has significant
Qingren Wang +4 more
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Automatic speech recognition with deep neural networks for impaired speech [PDF]
, 2016 The final publication is available at https://link.springer.com/chapter/10.1007%2F978-3-319-49169-1_10Automatic Speech Recognition has reached almost human performance in some controlled scenarios.
España-i-Bonet, Cristina +1 more
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