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Artificial Intelligence and Speech Technology -

Artificial Intelligence and Speech Technology

5th International Conference, AIST 2023, Delhi, India, December 26–27, 2023, Proceedings, Part I
Buch | Softcover
XXI, 478 Seiten
2024 | 2024
Springer International Publishing (Verlag)
978-3-031-75163-9 (ISBN)
CHF 127,30 inkl. MwSt
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This two-volume set, CCIS 2267 and 2268, constitutes the refereed proceedings of 5th International Conference on Artificial Intelligence and Speech Technology, AIST 2023, held in Delhi, India, during December 26-27, 2023. 

The 71 papers presented in two volumes were carefully reviewed and selected from 235 submissions. Part I focuses on Speech Technology using AI and Part II focuses on AI innovations for CV and NLP. These volumes are organized in the following topical sections: 

Part I: Trends and Applications in Speech Processing; Recent Trends in Speech and NLP; Emerging trends in Speech Processing; Advances in Computational Linguistics and NLP. 

Part II: Recent Trends in Machine Learning and Deep Learning; Analysis using Hybrid technologies with Artificial Intelligence; Exploring New Horizons in Computer Vision Research; Applications of Machine Learning and Deep Learning.  

.- An Efficient Deep Learning based Seq2Seq Model for Abstractive Text summarization.
.- Text Scribe: Unveiling New Dimensions in Text Summarization.
.- GRUbBD-SM: Gated Recurrent Unit based Bot Detection on social media.
.- Scaling Language Boundaries: A Comparative Analysis of Multilingual Question-Answering Capabilities in Large Language Models.
.- Performing Text Segmentation to Improve OCR on Multi Scene Text.
.- Deep Learning Based Multilingual Voice Recognition System and Analytics for Organization Surveys.
.- Speech Emotion Recognition using Convolutional Neural Networks.
.- Hybrid Approach to The Personification of dialogue Agents.
.- MelSpectroNet: Enhancing Voice Authentication Security with AI-based Siamese Model and Noise Reduction for Seamless User Experience.
.- A framework for Information Retrieval using Domain Specific Dictionary: Illustration through enhancing the Intelligence Cycle.
.- Text-Independent Voiceprints Identification using Feed- Forward Back-propagation with layered strategies.
.- Email Bot- Voice Based Email System for Blind.
.- Empowering Hate Speech Detection: A Comparative Exploration of Deep Learning Models.
.- Hate Speech Detection Using Glove and BERT.
.- Santali Vowel Recognition: An Under-Resourced Tribal Language.
.- Revolutionizing Writing: Personalized Neural Classifier for Handwritten Text.
.- Hindi Speech Recognition using Deep Learning: A Review.
.- A Comprehensive Review of Instructional Tools and Applications for Dyslexic Learners.
.- Deep Learning-based Speech Recognition Models: Review.
.- Analysis of Acoustic Features for Gender Identification using Punjabi Speech Dataset.
.- Context Based Anaphora Resolution of English Discourses using Rule Based Approach.
.- Enhancing Named Entity Recognition with DistilBERT and Attention Ensemble Fusion.
.- Explaining Spectrograms in Machine Learning: A Study on Neural Networks for Speech Classification.
.- Speech Recognition using Adaptation of Whisper Models.
.- Voice Stress Analysis using Machine Learning.
.- Efficient Real-Time Indian Sign Language Fingerspelling Recognition in Natural Settings using Heuristics.
.- A Novel and Intelligent approach for Indian Locale Based Text-to-Speech Model by hybridizing Wave Net and Wave Glow with Mel-Spectrogram Analysis.
.- Optimization of Indian Sign Language Detection using Data Generators.
.- A Comparative Analysis of Deep Learning Architecture for Accurate Gender Classification using Vocal Data.
.- A Comprehensive Analysis on Kaldi-Based Speech Recognition for Low Resource Indian Languages.
.- Comparative Analysis of Deep Learning Models for Text Summarization on Hindi Corpus.
.- Tune into Your Feelings: NLP-Powered Emotion Driven Music Recommender System.
.- Recent Trends in text to Speech Synthesis in Context with Indian Languages.
.- Advanced Speech Emotion Recognition in Malayalam Accented Speech: Analyzing Unsupervised and Supervised Approaches.

Erscheint lt. Verlag 6.12.2024
Reihe/Serie Communications in Computer and Information Science
Zusatzinfo XX, 459 p.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte adapting LLMs for speech tasks • Artificial Intelligence • compressed sensing (for Speech and/or Image Processing) • computer vision and speech recognition • Deep learning • Deep Learning for Image Recognition • generative adversarial networks (GANs) in computer vision • machine learning • medical imaging and AI • multimodal AI: integrating vision and speech • multimodal information retrieval • natural language processing based tools and applications • speech data collection and annotation • Speech Recognition • speech recognition with LLMs • Speech Synthesis • Speech Technology • speech/text language translation • Text-to-Speech Synthesis • transfer learning and fine-tuning techniques for ChatGPT
ISBN-10 3-031-75163-9 / 3031751639
ISBN-13 978-3-031-75163-9 / 9783031751639
Zustand Neuware
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