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136 - Including Signed Languages in NLP, with Kayo Yin and Malihe Alikhani
Manage episode 329056383 series 1452120
Contenido proporcionado por NLP Highlights and Allen Institute for Artificial Intelligence. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente NLP Highlights and Allen Institute for Artificial Intelligence o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In this episode, we talk with Kayo Yin, an incoming PhD at Berkeley, and Malihe Alikhani, an assistant professor at the University of Pittsburgh, about opportunities for the NLP community to contribute to Sign Language Processing (SLP). We talked about history and misconceptions about sign languages, high-level similarities and differences between spoken and sign languages, distinct linguistic features of signed languages, representations, computational resources, SLP tasks, and suggestions for better design and implementation of SLP models.
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Manage episode 329056383 series 1452120
Contenido proporcionado por NLP Highlights and Allen Institute for Artificial Intelligence. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente NLP Highlights and Allen Institute for Artificial Intelligence o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In this episode, we talk with Kayo Yin, an incoming PhD at Berkeley, and Malihe Alikhani, an assistant professor at the University of Pittsburgh, about opportunities for the NLP community to contribute to Sign Language Processing (SLP). We talked about history and misconceptions about sign languages, high-level similarities and differences between spoken and sign languages, distinct linguistic features of signed languages, representations, computational resources, SLP tasks, and suggestions for better design and implementation of SLP models.
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Similar a NLP Highlights
Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
…
continue reading
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…
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…
continue reading
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continue reading
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