{"product_id":"speech-and-computer-9783032079589","title":"Speech and Computer","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003e.- Automatic Speech Recognition.\u003c\/strong\u003e\u003cbr\u003e.- In-Domain SSL Pre-Training and Streaming ASR: Application to Air Traffic Control Communications.\u003cbr\u003e.- Evaluating the Performance of Several ASR Systems in Environmental and Industrial Noise.\u003cbr\u003e.- Ground Truth-Free WER Prediction for ASR via Audio Quality and Model Confidence Features.\u003cbr\u003e.- Enhancing Speech Recognition through Text-to-Speech and Voice Conversion Augmentation.\u003cbr\u003e.- Best Data is more Supervised Data - Even for Hungarian ASR.\u003cbr\u003e.- Arabic ASR on the SADA Large-Scale Arabic Speech Corpus with Transformer-based Models.\u003cbr\u003e\u003cstrong\u003e.- Speech Processing for Under-Resourced Languages.\u003c\/strong\u003e\u003cbr\u003e.- Effect of Increased Temporal Resolution on Speech Recognition for French Quebec using Features from Speech Self-Supervised Learning Models.\u003cbr\u003e.- Modeling Intra-Word Code-Switching for Karelian ASR.\u003cbr\u003e.- Improving Whisper-based Serbian ASR using Synthetic Speech.\u003cbr\u003e.- Domain Knowledge and Language Embeddings for Low-Resource Multilingual Phoneme ASR.\u003cbr\u003e.- Whistler Identification in Whistled Spanish (Silbo): A Case Study.\u003cbr\u003e\u003cstrong\u003e.- Digital Speech Processing.\u003c\/strong\u003e\u003cbr\u003e.- PinkVocalTransformer: Neural Acoustic-to-Articulatory Inversion based on the Pink Trombone.\u003cbr\u003e.- CrossMP-SENet: Transformer-based Cross-Attention for Joint Magnitude-Phase Speech Enhancement. \u003cbr\u003e.- Adaptive Singing Voice Enhancement for Live Stages.\u003cbr\u003e.- Revealing the Hidden Temporal Structure of HubertSoft Embeddings based on the Russian Phonetic Corpus.\u003cbr\u003e\u003cstrong\u003e.- Natural Language Processing.\u003c\/strong\u003e\u003cbr\u003e.- Analyzing Web-Scraped and Generated Inputs for Automatic and Scalable Intent Classification.\u003cbr\u003e.- Enhancing Retrieval Performance via LLM Hard-Negative Filtering.\u003cbr\u003e.- Sector-Wise Backpropagation for Low-Resource Text Classification in Deep Models.\u003cbr\u003e.- High-Frequency Multiword Units and the Typological Distribution of Multiword Units in Spoken Russian.\u003cbr\u003e.- Estimation of the Genre Composition of the English Subcorpus of the Google Books Ngram.\u003cbr\u003e\u003cstrong\u003e.- Multimodal Systems.\u003c\/strong\u003e\u003cbr\u003e.- Ensembling Synchronisation-based and Face-Voice Association Paradigms for Robust Active Speaker Detection in Egocentric Recordings.\u003cbr\u003e.- Phonetic and Visual Characteristics of Cognitive Load.\u003cbr\u003e.- Cognitive Humor Processing in the Russian and English Internet Meme Chatting: EEG Study.\u003cbr\u003e.- Saudi Sign Language Translation Using T5.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":52151402234199,"sku":"9783032079589","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/speech-and-computer-9783032079589","provider":"Book Curl","version":"1.0","type":"link"}