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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...89 Hits 1 – 20 of 1.765 1 RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION Mdhaffar, Salima; Bonastre, Jean-François; Tommasi, Marc... In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022) BASE Show details 2 Hippocampal and auditory contributions to speech segmentation Ramos-Escobar, Neus; Mercier, Manuel; Trébuchon-Fonséca, Agnès; Rodriguez-Fornells, Antoni; François, Clément; Schön, Daniele In: ISSN: 0010-9452 ; Cortex ; https://hal.archives-ouvertes.fr/hal-03604957 ; Cortex, Elsevier, 2022, ⟨10.1016/j.cortex.2022.01.017⟩ (2022) Abstract: International audience ; Statistical learning has been proposed as a mechanism to structure and segment the continuous flow of information in several sensory modalities. Previous studies proposed that the medial temporal lobe, and in particular the hippocampus, may be crucial to parse the stream in the visual modality. However, the involvement of the hippocampus in auditory statistical learning, and specifically in speech segmentation is less clear. To explore the role of the hippocampus in speech segmentation based on statistical learning, we exposed seven pharmaco-resistant temporal lobe epilepsy patients to a continuous stream of trisyllabic pseudowords and recorded intracranial stereotaxic electro-encephalography (sEEG). We used frequency-tagging analysis to quantify neuronal synchronization of the hippocampus and auditory regions to the temporal structure of words and syllables of the stream. Results show that while auditory regions highly respond to syllable frequency, the hippocampus responds mostly to word frequency. These findings provide direct evidence of the involvement of the hippocampus in speech segmentation process and suggest a hierarchical organization of auditory information during speech processing. Keyword: [SCCO]Cognitive science; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; frequency tagging; hippocampus; sEEG; speech segmentation; Statistical Learning URL: https://hal.archives-ouvertes.fr/hal-03604957/document https://hal.archives-ouvertes.fr/hal-03604957/file/CORTEX-D-21-00111_R1.pdf https://hal.archives-ouvertes.fr/hal-03604957 https://doi.org/10.1016/j.cortex.2022.01.017 BASE Hide details 3 Cross-lingual few-shot hate speech and offensive language detection using meta learning Mozafari, Marzieh; Farahbakhsh, Reza; Crespi, Noel In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022) BASE Show details 4 МОНОЛОГИЧЕСКАЯ РЕЧЬ С ТОЧКИ ЗРЕНИЯ УЧЁНЫХ ... : MONOLOGICAL SPEECH FROM THE POINT OF VIEW OF SCIENTISTS ... Н. И. Шадманова. - : Academic research in educational sciences, 2022 BASE Show details 5 A comparative study of several parameterizations for speaker recognition ... Faundez-Zanuy, Marcos. - : arXiv, 2022 BASE Show details 6 Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ... Lee, Hung-Shin; Tsao, Yu; Jeng, Shyh-Kang. - : arXiv, 2022 BASE Show details 7 REYD Yiddish TTS Corpus ... Unkn Unknown. - : Centre for Speech Technology Research (CSTR), 2022 BASE Show details 8 Data From: A Protracted Developmental Trajectory for English-Learning Children’s Detection of Consonant Mispronunciations in Newly Learned Words Quam, Carolyn; Swingley, Daniel In: Speech and Hearing Sciences Faculty Datasets (2022) BASE Show details 9 Intoxication and pitch control in tonal and non-tonal language speakers ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 10 Materials for Tang et al. (2022) ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 11 Dataset for Tang et al. (2022) ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 12 COLORINCO ... , Caudrelier. - : Open Science Framework, 2022 BASE Show details 13 Learning and controlling the source-filter representation of speech with a variational autoencoder ... Sadok, Samir; Leglaive, Simon; Girin, Laurent. - : arXiv, 2022 BASE Show details 14 Correcting Misproducted Speech using Spectrogram Inpainting ... Ben-Simon, Talia; Kreuk, Felix; Awwad, Faten. - : arXiv, 2022 BASE Show details 15 The 2021 NIST Speaker Recognition Evaluation ... Sadjadi, Seyed Omid; Greenberg, Craig; Singer, Elliot. - : arXiv, 2022 BASE Show details 16 Multilingual and Multimodal Abuse Detection ... Sharon, Rini; Shah, Heet; Mukherjee, Debdoot. - : arXiv, 2022 BASE Show details 17 WavThruVec: Latent speech representation as intermediate features for neural speech synthesis ... Siuzdak, Hubert; Dura, Piotr; van Rijn, Pol. - : arXiv, 2022 BASE Show details 18 CTA-RNN: Channel and Temporal-wise Attention RNN Leveraging Pre-trained ASR Embeddings for Speech Emotion Recognition ... Chen, Chengxin; Zhang, Pengyuan. - : arXiv, 2022 BASE Show details 19 Fine-grained Noise Control for Multispeaker Speech Synthesis ... Nikitaras, Karolos; Vamvoukakis, Georgios; Ellinas, Nikolaos. - : arXiv, 2022 BASE Show details 20 Emotion Intensity and its Control for Emotional Voice Conversion ... Zhou, Kun; Sisman, Berrak; Rana, Rajib. - : arXiv, 2022 BASE Show details Page: 1 2 3 4 5...89

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