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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 Hits 1 – 12 of 12 1 The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units Dunbar, Ewan; Karadayi, Julien; Bernard, Mathieu... In: Interspeech 2020 - Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02962224 ; Interspeech 2020 - Conference of the International Speech Communication Association, Oct 2020, Shangai / Virtual, China (2020) BASE Show details 2 Phonemic transcription of low-resource languages: To what extent can preprocessing be automated? Wisniewski, Guillaume; Michaud, Alexis; Guillaume, Séverine In: 1st Joint SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) Workshop ; https://halshs.archives-ouvertes.fr/hal-02513914 ; 1st Joint SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) Workshop, 2020, Marseille, France. pp.306-315 ; https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/SLTUCCURLbook.pdf (2020) BASE Show details 3 Transformer VQ-VAE for Unsupervised Unit Discovery and Speech Synthesis: ZeroSpeech 2020 Challenge ... Tjandra, Andros; Sakti, Sakriani; Nakamura, Satoshi. - : arXiv, 2020 BASE Show details 4 Phonemic transcription of low-resource languages: To what extent can preprocessing be automated? Wisniewski, Guillaume; Michaud, Alexis; Guillaume, Séverine In: 1st Joint SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) Workshop ; https://halshs.archives-ouvertes.fr/hal-02513914 ; 1st Joint SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) Workshop, 2020, Marseille, France. pp.306-315 ; https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/SLTUCCURLbook.pdf (2020) BASE Show details 5 The Zero Resource Speech Challenge 2019: TTS without T Dunbar, Ewan; Algayres, Robin; Karadayi, Julien... In: Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02274112 ; Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019) BASE Show details 6 A Speaking Atlas of Indigenous Languages of France and its Overseas Boula De Mareüil, Philippe; Vernier, Frédéric; Adda, Gilles... In: LT4All 2019, collection of research papers ; Language Technologies for All (LT4All) Enabling Language Diversity & Multilingualism Worldwide ; https://hal.archives-ouvertes.fr/hal-03099667 ; Language Technologies for All (LT4All) Enabling Language Diversity & Multilingualism Worldwide, Dec 2019, Paris, France. pp.155-159 ; https://lt4all.elra.info/proceedings/lt4all2019/ (2019) BASE Show details 7 Speech-to-speech Translation between Untranscribed Unknown Languages ... Tjandra, Andros; Sakti, Sakriani; Nakamura, Satoshi. - : arXiv, 2019 BASE Show details 8 Towards Machine Speech-to-speech Translation Nakamura, Satoshi; Sudoh, Katsuhito; Sakti, Sakriani. - 2019 BASE Show details 9 Local Monotonic Attention Mechanism for End-to-End Speech and Language Processing ... Tjandra, Andros; Sakti, Sakriani; Nakamura, Satoshi. - : arXiv, 2017 Abstract: Recently, encoder-decoder neural networks have shown impressive performance on many sequence-related tasks. The architecture commonly uses an attentional mechanism which allows the model to learn alignments between the source and the target sequence. Most attentional mechanisms used today is based on a global attention property which requires a computation of a weighted summarization of the whole input sequence generated by encoder states. However, it is computationally expensive and often produces misalignment on the longer input sequence. Furthermore, it does not fit with monotonous or left-to-right nature in several tasks, such as automatic speech recognition (ASR), grapheme-to-phoneme (G2P), etc. In this paper, we propose a novel attention mechanism that has local and monotonic properties. Various ways to control those properties are also explored. Experimental results on ASR, G2P and machine translation between two languages with similar sentence structures, demonstrate that the proposed encoder-decoder ... : Accepted at IJCNLP 2017 --- (V2: added more experiments on G2P & MT) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1705.08091 https://arxiv.org/abs/1705.08091 BASE Hide details 10 Listening while Speaking: Speech Chain by Deep Learning ... Tjandra, Andros; Sakti, Sakriani; Nakamura, Satoshi. - : arXiv, 2017 BASE Show details 11 Context Awareness and Priority Control for ITS based on Automatic Speech Recognition Sakti, Sakriani; Shagdar, Oyunchimeg; Nashashibi, Fawzi... In: International conference on ITS Telecommunications ; https://hal.inria.fr/hal-01225312 ; International conference on ITS Telecommunications, Dec 2015, Copenhagen, Denmark ; http://www.itst-conf.org/ (2015) BASE Show details 12 A-STAR: Toward translating Asian spoken languages Sakti, Sakriani; Paul, Michael; Finch, Andrew... In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 27 (2013) 2, 509-527 OLC Linguistik Show details

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