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Man-machine speech communication17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Man-machine speech communicationedited by Ling Zhenhua ... [et al.].
Reminder of title:	17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022 : proceedings /
remainder title:	NCMMSC 2022
other author:	Zhenhua, Ling.
corporate name:
Published:	Singapore :Springer Nature Singapore :2023.
Description:	1 online resource (xi, 332 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computational linguistics
Online resource:	https://doi.org/10.1007/978-981-99-2401-1
ISBN:	9789819924011$q(electronic bk.)

Man-machine speech communication17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022 : proceedings /
Man-machine speech communication17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022 : proceedings /[electronic resource] :NCMMSC 2022edited by Ling Zhenhua ... [et al.]. - Singapore :Springer Nature Singapore :2023. - 1 online resource (xi, 332 p.) :ill., digital ;24 cm. - Communications in computer and information science,17651865-0937 ;. - Communications in computer and information science ;229..

MCPN: A Multiple Cross-Perception Network for Real-Time Emotion Recognition in Conversation -- Baby Cry Recognition Based on Acoustic Segment Model -- A Multi-feature Sets Fusion Strategy with Similar Samples Removal for Snore Sound Classification -- Multi-Hypergraph Neural Networks for Emotion Recognition in Multi-Party Conversations -- Using Emoji as an Emotion Modality in Text-Based Depression Detection -- Source-Filter-Based Generative Adversarial Neural Vocoder for High Fidelity Speech Synthesis -- Semantic enhancement framework for robust speech recognition -- Achieving Timestamp Prediction While Recognizing with Non-Autoregressive End-to-End ASR Model -- Predictive AutoEncoders are Context-Aware Unsupervised Anomalous Sound Detectors -- A pipelined framework with serialized output training for overlapping speech recognition -- Adversarial Training Based on Meta-Learning in Unseen Domains for Speaker Verification -- Multi-Speaker Multi-Style Speech Synthesis with Timbre and Style Disentanglement -- Multiple Confidence Gates for Joint Training of SE and ASR -- Detecting Escalation Level from Speech with Transfer Learning and Acoustic-Linguistic Information Fusion -- Pre-training Techniques For Improving Text-to-Speech Synthesis By Automatic Speech Recognition Based Data Enhancement -- A Time-Frequency Attention Mechanism with Subsidiary Information for Effective Speech Emotion Recognition -- Interplay between prosody and syntax-semantics: Evidence from the prosodic features of Mandarin tag questions -- Improving Fine-grained Emotion Control and Transfer with Gated Emotion Representations in Speech Synthesis -- Violence Detection through Fusing Visual Information to Auditory Scene -- Mongolian Text-to-Speech Challenge under Low-Resource Scenario for NCMMSC2022 -- VC-AUG Voice Conversion based Data Augmentation for Text-Dependent Speaker Veriﬁcation -- Transformer-based potential emotional relation mining network for emotion recognition in conversation -- FastFoley Non-Autoregressive Foley Sound Generation Based On Visual Semantics -- Structured Hierarchical Dialogue Policy with Graph Neural Networks -- Deep Reinforcement Learning for On-line Dialogue State Tracking -- Dual Learning for Dialogue State Tracking -- Automatic Stress Annotation and Prediction For Expressive Mandarin TTS -- MnTTS2 An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset.

This book constitutes the refereed proceedings of the 17th National Conference on Man-Machine Speech Communication, NCMMSC 2022, held in China, in December 2022. The 21 full papers and 7 short papers included in this book were carefully reviewed and selected from 108 submissions. They were organized in topical sections as follows: MCPN: A Multiple Cross-Perception Network for Real-Time Emotion Recognition in Conversation -- Baby Cry Recognition Based on Acoustic Segment Model, MnTTS2 An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis Dataset.

ISBN: 9789819924011$q(electronic bk.)

Standard No.: 10.1007/978-981-99-2401-1doiSubjects--Topical Terms:

254690
Computational linguistics

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Man-machine speech communication17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022 : proceedings /
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