Atjaunināt sīkdatņu piekrišanu

E-grāmata: Man-Machine Speech Communication: 17th National Conference, NCMMSC 2022, Hefei, China, December 15-18, 2022, Proceedings

Edited by , Edited by , Edited by , Edited by
  • Formāts - EPUB+DRM
  • Cena: 83,27 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

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.
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 Verication.- 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.