Speech and Computer

25th International Conference, SPECOM 2023, Dharwad, India, November 29 – December 2, 2023, Proceedings, Part II

AvAlexey Karpov,K. Samudravijaya

Häftad, Engelska, 2023

Del 14339 i serien Lecture Notes in Computer Science

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Beskrivning

The two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.

Produktinformation

Utgivningsdatum:2023-11-22
Mått:155 x 235 x 32 mm
Vikt:890 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:568
Upplaga:23001
Förlag:Springer International Publishing AG
ISBN:9783031483110

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

Industrial Speech and Language Technology.- Analysing Breathing Patterns in Reading and Spontaneous Speech.- Audio-Visual Speaker Verification via Joint Cross Attention.- A Novel Scheme to Classify Read and Spontaneous Speech.- Analysis of a Hinglish ASR System’s Performance for Fraud Detection.- Anomaly Detection in Speech: A Comprehensive Approach for Enhanced Speech Analysis.- CAPTuring Accents: An Approach to Personalize Pronunciation Training for Learners with Different L1 Backgrounds.- Speech Technology for Under-Resourced Languages.- Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages.- Phone Durations Modeling for Livvi-Karelian ASR.- Significance of Indic Self-Supervised Speech Representations for Indic Under-Resourced ASR.- Study of Various End-to-End Keyword Spotting Systems on the Bengali language under Low-Resource Condition.- Bridging the Gap: Towards Linguistic Resource Development for the Low-Resource Lambani Language.- Studying the Effect of Frame-Level Concatenation of GFCC and TS-MFCC Features on Zero-Shot Children’s ASR.- Code-Mixed Text-to-Speech Synthesis under Low-Resource Constraints.- An End-to-End TTS Model in Chhattisgarhi, a Low-Resource Indian Language.- An ASR Corpus in Chhattisgarhi, a Low Resource Indian Language.- Cross Lingual Style Transfer using Multiscale Loss Function for Soliga: A Low Resource Tribal Language.- Preliminary Analysis of Lambani Vowels and Vowel Classification using Acoustic Feature.- Curriculum Learning based Approach for Faster Convergence of TTS Model.- Rhythm Measures and Language Endangerment: the Case of Deori.- Konkani Phonetic Transcription System 1.0.- Speech Analysis and Synthesis.- E-TTS: Expressive Text-to-Speech Synthesis for Hindi using Data Augmentation.- Direct vs Cascaded Speech-to-Speech Translation using Transformer.- Deep Learning based Speech Quality Assessment Focusing on Noise Effects.- Quantifying the Emotional Landscape of Music with Three Dimensions.- Analysis of Mandarin vs. English Language for Emotional Voice Conversion.- Audio DeepFake Detection Employing Multiple Parametric Exponential Linear Units.- A Comparison of Learned Representations with Jointly Optimized VAE and DNN for Syllable Stress Detection.- On the Asymptotic Behaviour of the Speech Signal.- Improvement of Audio-Visual Keyword Spotting System Accuracy using Excitation Source Feature.- Developing a Question Answering System on the material of Holocaust survivors’ testimonies in Russian.- Enhancing Children’s Short Utterance based ASV using Data Augmentation Techniques and Feature Concatenation Approach.- Studying the Effectiveness of Data Augmentation and Frequency-DomainLinear Prediction Coefficients in Children’s Speaker Verification under Low-Resource Conditions.- Constant-Q based Harmonic and Pitch Features for Normal vs Pathological Infant Cry Classification.- Robustness of Whisper Features for Infant Cry Classification.- Speaker and Language Identification, Verification, and Diarization.- I-MSV 2022: Indic-Multilingual and Multi-Sensor Speaker Verification Challenge.- Multi-Task Learning over Mixup Variants for the Speaker Verification Task.- Exploring the Impact of Different Approaches for Spoken Dialect Identification of Konkani Language.- Adversarially Trained Hierarchical Attention Network for Domain-Invariant Spoken Language Identification.- Ensemble of Incremental System Enhancements for Robust Speaker Diarization in Code-Switched Real-Life Audios.- Enhancing Language Identification in Indian Context through Exploiting Learned Features with Wav2Vec2.0.- Design and Development of Voice OTP Authentication System.- End-to-End Native Language Identification using a Modified Vision Transformer(ViT) from L2 English Speech.- Dialect Identification in Ao using Modulation-based Representation.- Self-Supervised Speaker Verification Employing Augmentation Mix and Self-Augmented Training-based Clustering.