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Man-Machine Speech Communication: 19th National Conference, NCMMSC 2024, Urumqi, China, August 1518, 2024, Proceedings [Mīkstie vāki]

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  • Formāts: Paperback / softback, 400 pages, height x width: 235x155 mm, 102 Illustrations, color; 31 Illustrations, black and white; XIII, 400 p. 133 illus., 102 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2312
  • Izdošanas datums: 27-Dec-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819610443
  • ISBN-13: 9789819610440
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Man-Machine Speech Communication: 19th National Conference, NCMMSC 2024, Urumqi, China, August 1518, 2024, ProceedingsPalielināt
  • Formāts: Paperback / softback, 400 pages, height x width: 235x155 mm, 102 Illustrations, color; 31 Illustrations, black and white; XIII, 400 p. 133 illus., 102 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2312
  • Izdošanas datums: 27-Dec-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819610443
  • ISBN-13: 9789819610440
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Permanent link: https://www.kriso.lv/db/9789819610440.html
This book constitutes the refereed proceedings of the 19th National Conference on Man-Machine Speech Communication, NCMMSC 2024, held in Urumqi, China, during August 1518, 2024.





The 33 papers included in these proceedings were carefully reviewed and selected from 205 submissions. They deal with topics such as speech technology and large language models, audio processing, prosody modeling and dialogue systems. Key areas include speech recognition, speaker identification and verification, speech/sound/music synthesis, speech enhancement, sound event detection, multimodal systems, conversational AI, phonetics, phonology and prosody analysis, auditory processing, and acoustic scene modeling etc.
.- The Attention-Based Fusion of Master-Auxiliary Network for Speech
Enhancement.

.- M-CMGAN: Attempting to Use Mamba on Speech Enhancement.

.- A Backend-friendly On-device Multi-channel Speech Enhancement System with
IPD and PHM.

.- SESNet: A Speech Enhancement and Separation Network in Noisy Reverberant
Environments.

.- ASD-Diff: Unsupervised Anomalous Sound Detection With Masked Diffusion
Model.

.- Emergence of Hemispheric Asymmetries and Predictive Coding in the Neural
Mechanism of Speech Perception.

.- Phoneme Semantic Backdoor Attacks with Multiple Task Learning for Speech
Classification Task.

.- AESR: Speech Recognition With Speech Emotion Recogniting Learning.

.- A Comparative Analysis of Diphthong Acquisition in Standard Chinese by
Learners from the Belt and Road.

.- ESTVocoder: An Excitation-Spectral-Transformed Neural Vocoder Conditioned
on Mel Spectrogram.

.- Transformer-based Model for Auditory EEG Decoding.

.- A Neural Denoising Vocoder for Clean Waveform Generation from Noisy
Mel-Spectrogram based on Amplitude and Phase Predictions.

.- Sound Zone Control Based on a Kronecker Second-Order Tensor
Decomposition.

.- MCDubber: Multimodal Context-Aware Expressive Video Dubbing.

.- TeleSpeechPT: Large-Scale Chinese Multi-Dialect And Multi-Accent Speech
Pre-Training.

.- Investigation into the Impact of Speaker Adversarial Perturbation on
Speech Recognition.

.- Pruning and Quantization Enhanced Densely Connected Neural Network for
Efficient Acoustic Echo Cancellation.

.- Improved DOA Estimation of Sound Source of Small Amplitudes using a Single
Acoustic Vector Sensor.

.- Investigation on Training Strategy for Cross-Modal Large Language Models
with Speech and Text.

.- ExARN: Target Speaker Extraction with Attentive Recurrent Networks.

.- Tone Perception by Putonghua-Learning Preschool Children in South Xinjiang
Uyghur Autonomous Region.

.- Study on Prosodic Disambiguation of VP/NP Syntactic Structure by Chinese
EFL Learners.

.- An electroencephalogram-based study of neural responses to imagined speech
in Mandarin.

.- A Speech Corpus of Putonghua-Learning Preschoolers From the Uygur Ethnic
Group in South Xinjiang Uygur Autonomous Region of China.

.- Evaluation of Data Inconsistency for Multi-modal Sentiment Analysis.

.- LDMME: Latent Diffusion Model for Music Editing.

.- Emotion-Aware Prosodic Phrasing for Expressive Text-to-Speech.

.- Speech emotion recognition based on multi acoustic feature fusion.

.- DA-KWFormer: A Domain Adaptation Network with K-Weight Transformer for
Speech Emotion Recognition.

.- An Unsupervised Domain Adaptation Method based on Distribution Alignment
for Speaker Verification.

.- Cross-Model Knowledge Distillation and Metadata Fusion for Respiratory
Sound Classification.

.- Effect of Focus on Vowel Duration and Formant in Cantonese.

.- A Quantitative Parameter of Pronunciation, TVVF.