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Speech and Computer

28th International Conference, SPECOM 2026, Ohrid, North Macedonia, September 17–18, 2026, Proceedings, Part I

Medium: Buch
ISBN: 978-3-032-37866-8
Verlag: Springer
Erscheinungstermin: 29.10.2026
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This book 16934 - 16935 constitutes the refereed proceedings of the 28th International Conference on Speech and Computer SPECOM 2026 held in Ohrid, North Macedonia, during September 17–18, 2026.

The total of 65 papers included in the proceedings was carefully reviewed and selected from 99 submissions. They were organized in topical sections as follows:

Part 1: Automatic Speech Recognition; Speech Processing for Healthcare; Dysarthric Speech Analysis; Natural Language Processing; Processing Under-Resourced Languages.
Part 2: Computational Paralinguistics; Multimodal Analysis; Speech and Language Resources; Audio Signal Processing.

Produkteigenschaften

  • Artikelnummer: 9783032378668
  • Medium: Buch
  • ISBN: 978-3-032-37866-8
  • Verlag: Springer
  • Erscheinungstermin: 29.10.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Lecture Notes in Computer Science
  • Produktform: Kartoniert
  • Seiten: 477
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt

Themen

Autoren/Hrsg.

Herausgeber

.- Automatic Speech Recognition.
.- Understanding Personalization Gains in Whisper ASR.
.- Cross-Lingual Robustness of Zipformer: Czech and German ASR Benchmarking Study.
.- LoRA-Based Speech-Augmented Language Model Adaptation for Hungarian ASR.
.- A Corpus-Based Approach to Candidate Generation for Korean Dialect ASR Post-Processing.
.- How Robust are Modern Automatic Speech Recognizers to Domain and Temporal Mismatch? A Study on the Less-Resourced Slovenian Language.
.- Sequential Domain Adaptation of Whisper for Kazakh Academic Lecture Speech Recognition.
.- Speech Processing for Healthcare.
.- Emotion-Trajectory-Driven Segment Selection for Depression Severity Prediction.
.- Impact of Audio Codecs on Automatic Depression Detection: A Cross-Corpus Study.
.- Exploring Voice and Speech as ADHD Markers.
.- Electroglottographic Features of Children with ADHD: a Pilot Study.
.- Iterative LLM-based Improvement for French Clinical Interview Transcription and Speaker Diarization.
.- Exploiting Large Language Models in Safety-Critical Medical Helplines: a Study in Serbian and English.
.- Explainable Cognitive Impairments Classification in Russian Speech.
.- eGeMAPS-Based Detection of Alzheimer’s Disease in Russian Speech: A Pilot Study.
.- ASR Personalization in Pathological Voice: Accuracy, Efficiency, and Duration Effects.
.- Dysarthric Speech Analysis.
.- Effects of Dysarthria on Speech Prosody- A Case Study.
.- Prosodic Features for Classification of Normal vs. Dysarthric Speech.
.- Cross-Lingual Dysarthria Detection: Rigorous Evaluation Methodology and Transfer Analysis Across Four Languages.
.- VocalPlan-AV: A Two-Stage Audio-Visual Framework for Dysarthric ASR using Vocal-Plan Reconstruction.
.- Personalized Speech Recovery Tracking with Wav2vec 2.0: A Longitudinal Study on Head-and-Neck Surgery Patients.
.- Natural Language Processing.
.- A Multi-Stage Method for Training Semantic Search Models.
.- Comparing Large Language Models for Aspect-Based Sentiment Analysis of Student Experience from Russian-Language Online Course
Reviews.
.- Synchronic and Diachronic Models of Motivation Ratings of English Words.
.- AI vs. Human Emotional Narratives: A Comparative Study of Subclausal Units in LLM-Generated and Human Spoken Texts.
.- LEMON: Factor-Level Semantic Alignment for Graph–Text Pairs.
.- Processing Under-Resourced Languages.
.- Utilizing LLMs for Domain Specific Corpus Augmentation for Sorbian Languages.
.- A System for Automatic Transcription of Macedonian Parliamentary Speech.
.- Acoustic Distinctiveness of Dialects: A Machine–Learning Approach to Clustering Southern Min Varieties.
.- PA-Profile: What Makes ASR-Derived Speech-Sound-Disorder Screening Work? A Study in English and Low-Resource Language
Kannada.
.- Semantic Selection and Filtering of Pseudo-Labelled Data for Low-Resource Speech Translation.
.- A Comprehensive Objective Evaluation of Modern Text-to-Speech for Turkish using Speech Quality Assessment Models.
.- Multi-Style Child TTS: An Expressive Text-to-Speech System for Children in Low-Resource Scenarios.