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Artificial Intelligence and Speech Technology 5th International Conference, AIST 2023, Delhi, India, December 26–27, 2023, Proceedings, Part I

Aus der Reihe Communications in Computer and Information Science

87,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.11.2024

Abbildungen

XX, 212 illus., 141 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Amita Dev + weitere

Verlag

Springer

Seitenzahl

467

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

733 g

Sprache

Englisch

ISBN

978-3-031-75163-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.11.2024

Abbildungen

XX, 212 illus., 141 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Herausgeber

Verlag

Springer

Seitenzahl

467

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

733 g

Sprache

Englisch

ISBN

978-3-031-75163-9

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: [email protected]

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  • Produktbild: Artificial Intelligence and Speech Technology
  • Produktbild: Artificial Intelligence and Speech Technology

  • .- 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.