作者: 夾克怕包裹 時(shí)間: 2025-3-21 22:31
Jianquan Zhou,Yi Gao,Siyu Zhanglt of a careful research and extensive translation operation ensuring The alphabetical index of organisations throughout the entries are as accurate and up-to-date as possible. Eastern Europe and the c.rs. lists all entries in The Editors would like to express thanks to the huge alphabetical order i作者: condone 時(shí)間: 2025-3-22 04:14 作者: 小鹿 時(shí)間: 2025-3-22 07:21
,Semi-End-to-End Nested Named Entity Recognition from?Speech,se a span classifier to classify only the spans that start with the predicted heads in transcriptions. From the experimental results on the nested NER dataset of Chinese speech CNERTA, our semi-E2E approach gets the best .1 score (1.84% and 0.53% absolute points higher than E2E and pipeline respecti作者: 不透明 時(shí)間: 2025-3-22 08:54
,APNet2: High-Quality and?High-Efficiency Neural Vocoder with?Direct Prediction of?Amplitude and?Phantroduce a multi-resolution discriminator (MRD) into the GAN-based losses and optimize the form of certain losses. At a common configuration with a waveform sampling rate of 22.05 kHz and spectral frame shift of 256 points (i.e., approximately 11.6 ms), our proposed APNet2 vocoder outperforms the or作者: modest 時(shí)間: 2025-3-22 13:58
,A Fast Sampling Method in?Diffusion-Based Dance Generation Models,uences during the iteration process, and eventually concatenating multiple short sequences to form a longer one. Experimental results show that our improved sampling method not only makes the generation speed faster, but also maintains the quality of the dance movements.作者: Clumsy 時(shí)間: 2025-3-22 19:37 作者: DRILL 時(shí)間: 2025-3-22 23:09
Emotional Support Dialog System Through Recursive Interactions Among Large Language Models,tional support strategy, while the latter boasts strong reasoning capabilities and world knowledge. By interacting, our framework synergistically leverages the strengths of both models. Furthermore, we have integrated recursive units to maintain the continuity of dialogue strategy, working toward th作者: Vulnerary 時(shí)間: 2025-3-23 05:11
,Task-Adaptive Generative Adversarial Network Based Speech Dereverberation for?Robust Speech Recognie generator as a dereverberation system. By doing so, the corresponding output distribution will be more suitable for the recognition task. Experimental results on the REVERB corpus show that our proposed approach achieves a relative 18.6% and 8.6% word error rate reduction than the traditional GAN-作者: ENACT 時(shí)間: 2025-3-23 07:44
,A Framework Combining Separate and?Joint Training for?Neural Vocoder-Based Monaural Speech Enhancemhigh-fidelity, high-generation speed vocoder, which synthesizes the improved speech waveform. Following the pre-training of these two modules, they are stacked for joint training. Experimental results show the superiority of this approach in terms of speech quality, surpassing the performance of con作者: Barter 時(shí)間: 2025-3-23 11:11 作者: 瑣事 時(shí)間: 2025-3-23 17:36 作者: Mast-Cell 時(shí)間: 2025-3-23 20:54
Gongzhen Zou,Jun Du,Shutong Niu,Hang Chen,Yuling Ren,Qinglong Li,Ruibo Liu,Chin-Hui Lee作者: 無(wú)能的人 時(shí)間: 2025-3-23 23:06 作者: reptile 時(shí)間: 2025-3-24 04:21 作者: 減震 時(shí)間: 2025-3-24 07:02
Xiaoran Li,Zilu Guo,Jun Du,Chin-Hui Lee,Yu Gao,Wenbin Zhang作者: 不整齊 時(shí)間: 2025-3-24 13:57
Baochen Yang,Jiaqi Guo,Haoyu Li,Yu Xi,Qing Zhuo,Kai Yu作者: sacrum 時(shí)間: 2025-3-24 18:37 作者: notification 時(shí)間: 2025-3-24 22:08
Linhan Ma,Yongmao Zhang,Xinfa Zhu,Yi Lei,Ziqian Ning,Pengcheng Zhu,Lei Xie作者: 外向者 時(shí)間: 2025-3-24 23:17
Conference proceedings 2024, during?December 8–11, 2023..The? 20 full papers and 11 short papers included in this book were carefully reviewed and?selected from?117?submissions. They deal with topics such as speech recognition, synthesis, enhancement and coding, audio/music/singing synthesis, avatar, speaker recognition and v作者: Friction 時(shí)間: 2025-3-25 06:43
Ultra-Low Complexity Residue Echo and Noise Suppression Based on Recurrent Neural Network,ifferent topologies, feed in with different combinations of the far-end signal, microphone signal, predicted linear echo and residue error signal. The proposed RES models can achieve comparable echo cancellation and noise reduction capabilities to the AEC Challenge 2022 baseline model at a complexity lower than 5% of the baseline model.作者: 落葉劑 時(shí)間: 2025-3-25 09:54 作者: artless 時(shí)間: 2025-3-25 13:17 作者: Ergots 時(shí)間: 2025-3-25 17:19
,Data Augmentation by?Finite Element Analysis for?Enhanced Machine Anomalous Sound Detection,and the material of the medium is modified to acquire data from multiple domains. The experimental results on DCASE?2023 Task?2 dataset indicates a better performance from models trained using augmented data.作者: Fluctuate 時(shí)間: 2025-3-25 22:24
,End-to-End Streaming Customizable Keyword Spotting Based on?Text-Adaptive Neural Search,esults on various datasets show that our approach significantly outperforms both traditional post-processing baseline and the neural search baseline, meanwhile achieving a 44x search speedup compared to the traditional post-processing method.作者: champaign 時(shí)間: 2025-3-26 02:18
,Real-Time Automotive Engine Sound Simulation with?Deep Neural Network,modified griffin-lim algorithm at the frame level, which, with our proposed overlap-and-add feature, can bridge the phase gap between two frames. Experimental evaluations on our self-collected database validate the efficacy of the introduced approach.作者: Onerous 時(shí)間: 2025-3-26 05:41
,A Lightweight Music Source Separation Model with?Graph Convolution Network,and multiple .s, and also make a visualization analysis of the main components in the G-MSS network. Comparing with the other 13 methods on the MUSDB18 dataset, our proposed G-MSS achieves comparable separation performance while maintaining the lower amount of parameters.作者: SSRIS 時(shí)間: 2025-3-26 11:04 作者: CAMP 時(shí)間: 2025-3-26 15:54
,A Study on?Domain Adaptation for?Audio-Visual Speech Enhancement,-model fusion strategy to enhance the overall model performance further. Our system exhibited significant improvements in all objective metrics, including PESQ, STOI, and SiSDR, compared to almost all competing teams. As a result, our system ranked the 2nd place in the objective metrics comparison for track 1.作者: BARB 時(shí)間: 2025-3-26 19:16 作者: GROWL 時(shí)間: 2025-3-26 21:25
,Joint Speech and?Noise Estimation Using SNR-Adaptive Target Learning for?Deep-Learning-Based Speeche estimation network and validate the adaptability of the target learning strategy with the noise prediction branch. We demonstrate the effectiveness of our proposed method on a public benchmark, achieving a significant relative word error rate (WER) reduction of approximately 37% compared to the WER results obtained from unprocessed noisy speech.作者: Ventricle 時(shí)間: 2025-3-27 01:38
,Accent-VITS: Accent Transfer for?End-to-End TTS,e disentanglement of accent and speaker timbre becomes be more stable and effective. Experiments on multi-accent and Mandarin datasets show that Accent-VITS achieves higher speaker similarity, accent similarity and speech naturalness as compared with a strong baseline (Demos: .).作者: 鉆孔 時(shí)間: 2025-3-27 08:51 作者: Console 時(shí)間: 2025-3-27 10:46 作者: 6Applepolish 時(shí)間: 2025-3-27 16:03
,Semi-End-to-End Nested Named Entity Recognition from?Speech,rrors are inevitable. In the E2E approach, its annotation method poses a challenge to Automatic Speech Recognition (ASR) when Named Entities (NEs) are nested. This is because multiple special tokens without audio signals between words will exist, which may even cause ambiguity problems for NER. In t作者: paragon 時(shí)間: 2025-3-27 21:37
,A Lightweight Music Source Separation Model with?Graph Convolution Network,wever, most of them primarily focus on improving their separation performance, while ignoring the issue of model size in the real-world environments. For the application in the real-world environments, in this paper, we propose a lightweight network combined with the Graph convolutional network Atte作者: 用肘 時(shí)間: 2025-3-27 23:00
,Joint Time-Domain and?Frequency-Domain Progressive Learning for?Single-Channel Speech Enhancement alean target, which may introduce speech distortions and limit ASR performance. Meanwhile, these methods usually focus on either the time or frequency domain, ignoring their potential connections. To tackle these problems, we propose a joint time and frequency domain progressive learning (TFDPL) meth作者: Foregery 時(shí)間: 2025-3-28 02:38 作者: electrolyte 時(shí)間: 2025-3-28 09:41 作者: Palliation 時(shí)間: 2025-3-28 11:22
,Within- and Between-Class Sample Interpolation Based Supervised Metric Learning for?Speaker Verific methods may suffer from inadequate and low-quality sample pairs, resulting unsatisfactory speaker verification (SV) performance. To address this issue, we propose the data augmentation methods in the embedding space to guarantee sufficient and high-quality negative points for metric learning, terme作者: 斜谷 時(shí)間: 2025-3-28 17:17
,Joint Speech and?Noise Estimation Using SNR-Adaptive Target Learning for?Deep-Learning-Based Speech between speech enhancement (SE) and automatic speech recognition (ASR) modules. The progressive learning (PL) methods have revealed the importance of retaining residual noise in the training targets of the enhancement model to alleviate this mismatch. Inspired by this, we adopt an SNR-adaptive targ作者: placebo 時(shí)間: 2025-3-28 19:45 作者: 整潔 時(shí)間: 2025-3-29 01:57 作者: Orthodontics 時(shí)間: 2025-3-29 06:05
,End-to-End Streaming Customizable Keyword Spotting Based on?Text-Adaptive Neural Search,est-time customizable keyword spotting in streaming mode remains a great challenge due to the lack of pre-collected keyword-specific training data and the requirement of streaming detection output. In this paper, we propose a novel end-to-end text-adaptive neural search architecture with a multi-lab作者: osteopath 時(shí)間: 2025-3-29 07:42 作者: PAC 時(shí)間: 2025-3-29 14:31
Emotional Support Dialog System Through Recursive Interactions Among Large Language Models,t advancements in large language models (LLMs) have shown their significant potential in emotional support conversations. However, despite the impressive reasoning capabilities and extensive knowledge of LLMs, they fall short in using strategy and achieving overall goals in multi-turn counseling con作者: 不開(kāi)心 時(shí)間: 2025-3-29 16:40 作者: immunity 時(shí)間: 2025-3-29 23:44
,Real-Time Automotive Engine Sound Simulation with?Deep Neural Network,present a hybrid approach combining both sample-based and procedural methods. In the sample-based technique, the sound of an idle engine undergoes pitch-shifting proportional to the ratio of current RPM to idle RPM. For the procedural technique, deep neural networks fine-tune the amplitude of the en作者: 共和國(guó) 時(shí)間: 2025-3-30 01:12
,A Framework Combining Separate and?Joint Training for?Neural Vocoder-Based Monaural Speech Enhancemthe original phase spectrum. Nonetheless, this may introduce speech distortion. While the intricate nature of the multifaceted spectra and waveform characteristics presents formidable challenges in training. In this paper, we introduce a novel framework with the Mel-spectrogram serving as an interme作者: Aviary 時(shí)間: 2025-3-30 07:55 作者: AMEND 時(shí)間: 2025-3-30 11:33
,Multi-branch Network with?Cross-Domain Feature Fusion for?Anomalous Sound Detection,at detecting unknown machine anomalous sounds by learning the characteristics of the normal sounds using metainformation. In this paper, we propose a multi-branch network with cross-domain feature fusion (MBN-CFF) for self-supervised ASD task. The multi-branch network splits the complete feature rep作者: Wernickes-area 時(shí)間: 2025-3-30 14:14 作者: LUDE 時(shí)間: 2025-3-30 18:08
ta on over 3,000 organisations including Manufacturers, Foreign Trading arrangement of this Organisations, Banks, Ministries, Chambers of Commerce and Services. book Due to the change in the import/export laws in Eastern Europe it is now possible to trade directly with many This book has been arrang作者: COKE 時(shí)間: 2025-3-30 23:01 作者: 魔鬼在游行 時(shí)間: 2025-3-31 03:23
Min Zhang,XiaoSong Qiao,Yanqing Zhao,Chang Su,Yuang Li,Yinglu Li,Mengyao Piao,Song Peng,Shimin Tao,Huate to facilitate equivalency recognition for students transferring internationally for further study or for graduates seeking employment or career progression beyond borders. To meet this gap, a comprehensive Diploma Supplement emerged from a number of international meetings and agreements since t作者: 青石板 時(shí)間: 2025-3-31 08:27 作者: 雄辯 時(shí)間: 2025-3-31 10:46
Communications in Computer and Information Sciencehttp://image.papertrans.cn/m/image/622082.jpg作者: 浪蕩子 時(shí)間: 2025-3-31 15:59
978-981-97-0600-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: hypertension 時(shí)間: 2025-3-31 20:50
Man-Machine Speech Communication978-981-97-0601-3Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 譏諷 時(shí)間: 2025-3-31 23:33
10樓作者: Carbon-Monoxide 時(shí)間: 2025-4-1 05:17
10樓作者: echnic 時(shí)間: 2025-4-1 07:07
10樓
