1 |
How are visemes and graphemes integrated with speech sounds during spoken word recognition? ERP evidence for supra-additive responses during audiovisual compared to auditory speech processing
|
|
|
|
In: ISSN: 0093-934X ; EISSN: 1090-2155 ; Brain and Language ; https://hal.archives-ouvertes.fr/hal-03472191 ; Brain and Language, Elsevier, 2022, 225, ⟨10.1016/j.bandl.2021.105058⟩ (2022)
|
|
BASE
|
|
Show details
|
|
2 |
Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
|
|
|
|
In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-03578503 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapour, Singapore (2022)
|
|
BASE
|
|
Show details
|
|
3 |
Investigating the locus of transposed-phoneme effects using cross-modal priming
|
|
|
|
In: ISSN: 0001-6918 ; EISSN: 1873-6297 ; Acta Psychologica ; https://hal.archives-ouvertes.fr/hal-03619856 ; Acta Psychologica, Elsevier, 2022, 226, pp.103578. ⟨10.1016/j.actpsy.2022.103578⟩ (2022)
|
|
BASE
|
|
Show details
|
|
4 |
Potential of automatic speech processing technologies for early detection of oral language disorders: a meta-analytic review ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
A comparative study of several parameterizations for speaker recognition ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Speaker verification in mismatch training and testing conditions ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Speech Segmentation Optimization using Segmented Bilingual Speech Corpus for End-to-end Speech Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Estimating Vocal Tract Resonances of Synthesized High-Pitched Vowels Using CNN ...
|
|
|
|
BASE
|
|
Show details
|
|
9 |
A New Amharic Speech Emotion Dataset and Classification Benchmark ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks ...
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ...
|
|
|
|
BASE
|
|
Show details
|
|
13 |
LPC Augment: An LPC-Based ASR Data Augmentation Algorithm for Low and Zero-Resource Children's Dialects ...
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Automatic Dialect Density Estimation for African American English ...
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Data From: A Protracted Developmental Trajectory for English-Learning Children’s Detection of Consonant Mispronunciations in Newly Learned Words
|
|
|
|
In: Speech and Hearing Sciences Faculty Datasets (2022)
|
|
BASE
|
|
Show details
|
|
16 |
End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system ...
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems ...
|
|
|
|
Abstract:
Contextual biasing is an important and challenging task for end-to-end automatic speech recognition (ASR) systems, which aims to achieve better recognition performance by biasing the ASR system to particular context phrases such as person names, music list, proper nouns, etc. Existing methods mainly include contextual LM biasing and adding bias encoder into end-to-end ASR models. In this work, we introduce a novel approach to do contextual biasing by adding a contextual spelling correction model on top of the end-to-end ASR system. We incorporate contextual information into a sequence-to-sequence spelling correction model with a shared context encoder. Our proposed model includes two different mechanisms: autoregressive (AR) and non-autoregressive (NAR). We propose filtering algorithms to handle large-size context lists, and performance balancing mechanisms to control the biasing degree of the model. We demonstrate the proposed model is a general biasing solution which is domain-insensitive and can be ... : This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible ...
|
|
Keyword:
Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD
|
|
URL: https://dx.doi.org/10.48550/arxiv.2203.00888 https://arxiv.org/abs/2203.00888
|
|
BASE
|
|
Hide details
|
|
18 |
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation ...
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Automatic Detection of Speech Sound Disorder in Child Speech Using Posterior-based Speaker Representations ...
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
|
|
|
|
BASE
|
|
Show details
|
|
|
|