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A prospective study of associations between early fearfulness and perceptual sensitivity and later restricted and repetitive behaviours in infants with typical and elevated likelihood of Autism
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Semi-supervised cycle-consistency training for end-to-end ASR using unpaired speech
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Incorporating Temporal Information in Entailment Graph Mining ...
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Integrating Lexical Information into Entity Neighbourhood Representations for Relation Prediction ...
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Investigating the Mechanisms Driving Referent Selection and Retention in Toddlers at Typical and Elevated Likelihood for Autism Spectrum Disorder. ...
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Enforcing constraints for multi-lingual and cross-lingual speech-to-text systems
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Knowledge base integration in biomedical natural language processing applications
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Learning speech embeddings for speaker adaptation and speech understanding
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Modeling phones, keywords, topics and intents in spoken languages
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Investigating the Mechanisms Driving Referent Selection and Retention in Toddlers at Typical and Elevated Likelihood for Autism Spectrum Disorder.
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Infant EEG theta modulation predicts childhood intelligence
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Neural and behavioural indices of face processing in siblings of children with autism spectrum disorder (ASD): a longitudinal study from infancy to mid-childhood
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Speech technology for unwritten languages
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In: ISSN: 2329-9290 ; EISSN: 2329-9304 ; IEEE/ACM Transactions on Audio, Speech and Language Processing ; https://hal.inria.fr/hal-02480675 ; IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2020, ⟨10.1109/TASLP.2020.2973896⟩ (2020)
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Incorporating Temporal Information in Entailment Graph Mining ...
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How Phonotactics Affect Multilingual and Zero-shot ASR Performance ...
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That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages ...
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Abstract:
Only a handful of the world's languages are abundant with the resources that enable practical applications of speech processing technologies. One of the methods to overcome this problem is to use the resources existing in other languages to train a multilingual automatic speech recognition (ASR) model, which, intuitively, should learn some universal phonetic representations. In this work, we focus on gaining a deeper understanding of how general these representations might be, and how individual phones are getting improved in a multilingual setting. To that end, we select a phonetically diverse set of languages, and perform a series of monolingual, multilingual and crosslingual (zero-shot) experiments. The ASR is trained to recognize the International Phonetic Alphabet (IPA) token sequences. We observe significant improvements across all languages in the multilingual setting, and stark degradation in the crosslingual setting, where the model, among other errors, considers Javanese as a tone language. ... : Submitted to Interspeech 2020. For some reason, the ArXiv Latex engine rendered it in more than 4 pages ...
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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
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URL: https://dx.doi.org/10.48550/arxiv.2005.08118 https://arxiv.org/abs/2005.08118
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