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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8 9...567 Hits 81 – 100 of 11.324 81 Emotion Intensity and its Control for Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Rana, Rajib. - : arXiv, 2022 BASE Show details 82 Automatic Speech recognition for Speech Assessment of Preschool Children ... Abaskohi, Amirhossein; Mortazavi, Fatemeh; Moradi, Hadi. - : arXiv, 2022 BASE Show details 83 Deep Speech Based End-to-End Automated Speech Recognition (ASR) for Indian-English Accents ... Dubey, Priyank; Shah, Bilal. - : arXiv, 2022 BASE Show details 84 KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics ... Mussakhojayeva, Saida; Khassanov, Yerbolat; Varol, Huseyin Atakan. - : arXiv, 2022 BASE Show details 85 Automated speech tools for helping communities process restricted-access corpora for language revival efforts ... San, Nay; Bartelds, Martijn; Ògúnrèmí, Tolúlopé. - : arXiv, 2022 BASE Show details 86 Learning English with Peppa Pig ... Nikolaus, Mitja; Alishahi, Afra; Chrupała, Grzegorz. - : arXiv, 2022 BASE Show details 87 Separate What You Describe: Language-Queried Audio Source Separation ... Liu, Xubo; Liu, Haohe; Kong, Qiuqiang. - : arXiv, 2022 BASE Show details 88 A Complementary Joint Training Approach Using Unpaired Speech and Text for Low-Resource Automatic Speech Recognition ... Du, Ye-Qian; Zhang, Jie; Zhu, Qiu-Shi. - : arXiv, 2022 BASE Show details 89 Arabic Text-To-Speech (TTS) Data Preparation ... Masri, Hala Al; Za'ter, Muhy Eddin. - : arXiv, 2022 BASE Show details 90 The First Gospel, the Gospel of the Poor: A New Reconstruction of Q and Resolution of the Synoptic Problem based on Marcion's Early Luke ... Bilby, Mark G.. - : Zenodo, 2022 BASE Show details 91 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 92 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 93 Google Colab notebook ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 94 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 95 Google Colab notebook ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 96 REYD demo files ... Bleaman, Isaac. - : figshare, 2022 BASE Show details 97 Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training ... Sanabria, Ramon; Hsu, Wei-Ning; Baevski, Alexei. - : arXiv, 2022 BASE Show details 98 Low-dimensional representation of infant and adult vocalization acoustics ... Pagliarini, Silvia; Schneider, Sara; Kello, Christopher T.. - : arXiv, 2022 BASE Show details 99 Dual-Decoder Transformer For end-to-end Mandarin Chinese Speech Recognition with Pinyin and Character ... Yang, Zhao; Xi, Wei; Wang, Rui. - : arXiv, 2022 BASE Show details 100 Similarity and Content-based Phonetic Self Attention for Speech Recognition ... Shim, Kyuhong; Sung, Wonyong. - : arXiv, 2022 Abstract: Transformer-based speech recognition models have achieved great success due to the self-attention (SA) mechanism that utilizes every frame in the feature extraction process. Especially, SA heads in lower layers capture various phonetic characteristics by the query-key dot product, which is designed to compute the pairwise relationship between frames. In this paper, we propose a variant of SA to extract more representative phonetic features. The proposed phonetic self-attention (phSA) is composed of two different types of phonetic attention; one is similarity-based and the other is content-based. In short, similarity-based attention utilizes the correlation between frames while content-based attention only considers each frame without being affected by others. We identify which parts of the original dot product are related to two different attention patterns and improve each part by simple modifications. Our experiments on phoneme classification and speech recognition show that replacing SA with phSA for ... : Submitted to INTERSPEECH 2022 ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering URL: https://dx.doi.org/10.48550/arxiv.2203.10252 https://arxiv.org/abs/2203.10252 BASE Hide details Page: 1 2 3 4 5 6 7 8 9...567

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