{"product_id":"9783032079589","title":"Speech and Computer : 27th International Conference, SPECOM 2025, Szeged, Hungary, October 13-15, 2025, Proceedings, Part II (Lecture Notes in Computer Science)","description":"\u003cp\u003eThis two-set volume LNAI 16187 and 16188 constitutes the refereed proceedings of the 27th International Conference on Speech and Computer SPECOM 2025 held in Szeged, Hungary, during October 13 15, 2025.\u003c\/p\u003e\u003cp\u003eThe 47 full papers and 1 invited paper included in this book were carefully reviewed and selected from 77 submissions. The papers are organized in the following topical sections:  \u003c\/p\u003e\u003cp\u003ePart I: Invited Paper; Speech Perception and Synthesis; Computational Paralinguistics; Speech Processing for Healthcare; Speech and Language Resources; Speaker Recognition.\u003c\/p\u003e\u003cp\u003ePart II:  Automatic Speech Recognition; Speech Processing for Under-Resourced Languages; Digital Speech Processing; Natural Language Processing; Multimodal Systems.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003e.- Automatic Speech Recognition.\u003c\/strong\u003e\n.- In-Domain SSL Pre-Training and Streaming ASR: Application to Air Traffic Control Communications.\n.- Evaluating the Performance of Several ASR Systems in Environmental and Industrial Noise.\n.- Ground Truth-Free WER Prediction for ASR via Audio Quality and Model Confidence Features.\n.- Enhancing Speech Recognition through Text-to-Speech and Voice Conversion Augmentation.\n.- Best Data is more Supervised Data - Even for Hungarian ASR.\n.- Arabic ASR on the SADA Large-Scale Arabic Speech Corpus with Transformer-based Models.\n\u003cstrong\u003e.- Speech Processing for Under-Resourced Languages.\u003c\/strong\u003e\n.- Effect of Increased Temporal Resolution on Speech Recognition for French Quebec using Features from Speech Self-Supervised Learning Models.\n.- Modeling Intra-Word Code-Switching for Karelian ASR.\n.- Improving Whisper-based Serbian ASR using Synthetic Speech.\n.- Domain Knowledge and Language Embeddings for Low-Resource Multilingual Phoneme ASR.\n.- Whistler Identification in Whistled Spanish (Silbo): A Case Study.\n\u003cstrong\u003e.- Digital Speech Processing.\u003c\/strong\u003e\n.- PinkVocalTransformer: Neural Acoustic-to-Articulatory Inversion based on the Pink Trombone.\n.- CrossMP-SENet: Transformer-based Cross-Attention for Joint Magnitude-Phase Speech Enhancement. \n.- Adaptive Singing Voice Enhancement for Live Stages.\n.- Revealing the Hidden Temporal Structure of HubertSoft Embeddings based on the Russian Phonetic Corpus.\n\u003cstrong\u003e.- Natural Language Processing.\u003c\/strong\u003e\n.- Analyzing Web-Scraped and Generated Inputs for Automatic and Scalable Intent Classification.\n.- Enhancing Retrieval Performance via LLM Hard-Negative Filtering.\n.- Sector-Wise Backpropagation for Low-Resource Text Classification in Deep Models.\n.- High-Frequency Multiword Units and the Typological Distribution of Multiword Units in Spoken Russian.\n.- Estimation of the Genre Composition of the English Subcorpus of the Google Books Ngram.\n\u003cstrong\u003e.- Multimodal Systems.\u003c\/strong\u003e\n.- Ensembling Synchronisation-based and Face-Voice Association Paradigms for Robust Active Speaker Detection in Egocentric Recordings.\n.- Phonetic and Visual Characteristics of Cognitive Load.\n.- Cognitive Humor Processing in the Russian and English Internet Meme Chatting: EEG Study.\n.- Saudi Sign Language Translation Using T5.\u003c\/p\u003e","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48870418153707,"sku":"00000_00000_00000_00000","price":164.78,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9783032079589-1.jpg?v=1781718053","url":"https:\/\/kinokuniya.com.sg\/products\/9783032079589","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}