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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...395 Hits 1 – 20 of 7.887 1 Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice ... Borg, Markus; Bengtsson, Johan; Österling, Harald. - : arXiv, 2022 BASE Show details 2 Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang ... Keidar, Daphna; Opedal, Andreas; Jin, Zhijing. - : arXiv, 2022 BASE Show details 3 Cross-Lingual Phrase Retrieval ... Zheng, Heqi; Zhang, Xiao; Chi, Zewen. - : arXiv, 2022 BASE Show details 4 Improve Sentence Alignment by Divide-and-conquer ... Zhang, Wu. - : arXiv, 2022 BASE Show details 5 Graph Neural Networks for Multiparallel Word Alignment ... Imani, Ayyoob; Şenel, Lütfi Kerem; Sabet, Masoud Jalili. - : arXiv, 2022 BASE Show details 6 Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip Translation ... Lai, Siyu; Yang, Zhen; Meng, Fandong. - : arXiv, 2022 BASE Show details 7 Pirá: A Bilingual Portuguese-English Dataset for Question-Answering about the Ocean ... Paschoal, André F. A.; Pirozelli, Paulo; Freire, Valdinei. - : arXiv, 2022 BASE Show details 8 A Neural Pairwise Ranking Model for Readability Assessment ... Lee, Justin; Vajjala, Sowmya. - : arXiv, 2022 BASE Show details 9 A bilingual approach to specialised adjectives through word embeddings in the karstology domain ... Simeunović, Larisa Grčić; Martinc, Matej; Vintar, Špela. - : arXiv, 2022 BASE Show details 10 Universal Conditional Masked Language Pre-training for Neural Machine Translation ... Li, Pengfei; Li, Liangyou; Zhang, Meng. - : arXiv, 2022 BASE Show details 11 SMDT: Selective Memory-Augmented Neural Document Translation ... Zhang, Xu; Yang, Jian; Huang, Haoyang. - : arXiv, 2022 BASE Show details 12 Learning How to Translate North Korean through South Korean ... Kim, Hwichan; Moon, Sangwhan; Okazaki, Naoaki. - : arXiv, 2022 BASE Show details 13 When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation? ... Mao, Zhuoyuan; Chu, Chenhui; Dabre, Raj. - : arXiv, 2022 BASE Show details 14 Conditional Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation ... Zhang, Songming; Liu, Yijin; Meng, Fandong. - : arXiv, 2022 BASE Show details 15 Can Synthetic Translations Improve Bitext Quality? ... Briakou, Eleftheria; Carpuat, Marine. - : arXiv, 2022 BASE Show details 16 MSCTD: A Multimodal Sentiment Chat Translation Dataset ... Liang, Yunlong; Meng, Fandong; Xu, Jinan. - : arXiv, 2022 BASE Show details 17 Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation ... Fukuda, Ryo; Sudoh, Katsuhito; Nakamura, Satoshi. - : arXiv, 2022 BASE Show details 18 A New Amharic Speech Emotion Dataset and Classification Benchmark ... Retta, Ephrem A.; Almekhlafi, Eiad; Sutcliffe, Richard. - : arXiv, 2022 BASE Show details 19 Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks ... Moisio, Anssi; Porjazovski, Dejan; Rouhe, Aku. - : arXiv, 2022 BASE Show details 20 The Norwegian Parliamentary Speech Corpus ... Solberg, Per Erik; Ortiz, Pablo. - : arXiv, 2022 Abstract: The Norwegian Parliamentary Speech Corpus (NPSC) is a speech dataset with recordings of meetings from Stortinget, the Norwegian parliament. It is the first, publicly available dataset containing unscripted, Norwegian speech designed for training of automatic speech recognition (ASR) systems. The recordings are manually transcribed and annotated with language codes and speakers, and there are detailed metadata about the speakers. The transcriptions exist in both normalized and non-normalized form, and non-standardized words are explicitly marked and annotated with standardized equivalents. To test the usefulness of this dataset, we have compared an ASR system trained on the NPSC with a baseline system trained on only manuscript-read speech. These systems were tested on an independent dataset containing spontaneous, dialectal speech. The NPSC-trained system performed significantly better, with a 22.9% relative improvement in word error rate (WER). Moreover, training on the NPSC is shown to have a ... : 6 pages, submitted to LREC 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; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2201.10881 https://arxiv.org/abs/2201.10881 BASE Hide details Page: 1 2 3 4 5...395

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