{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/encoding-of-phonology-in-a-recurrent-neural","title":"Encoding of phonology in a recurrent neural model of grounded speech","arxiv_id":"1706.03815","date":"2017-06-12","proceeding":"CONLL 2017 8","authors":["Afra Alishahi","Marie Barking","Grzegorz Chrupała"],"abstract":"We study the representation and encoding of phonemes in a recurrent neural\nnetwork model of grounded speech. We use a model which processes images and\ntheir spoken descriptions, and projects the visual and auditory representations\ninto the same semantic space. We perform a number of analyses on how\ninformation about individual phonemes is encoded in the MFCC features extracted\nfrom the speech signal, and the activations of the layers of the model. Via\nexperiments with phoneme decoding and phoneme discrimination we show that\nphoneme representations are most salient in the lower layers of the model,\nwhere low-level signals are processed at a fine-grained level, although a large\namount of phonological information is retain at the top recurrent layer. We\nfurther find out that the attention mechanism following the top recurrent layer\nsignificantly attenuates encoding of phonology and makes the utterance\nembeddings much more invariant to synonymy. Moreover, a hierarchical clustering\nof phoneme representations learned by the network shows an organizational\nstructure of phonemes similar to those proposed in linguistics.","url_abs":"http://arxiv.org/abs/1706.03815v2","url_pdf":"http://arxiv.org/pdf/1706.03815v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"encoding-of-phonology-in-a-recurrent-neural","repo_url":"https://github.com/gchrupala/encoding-of-phonology","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1706.03815","atlas_url":"https://app.syntology.ai/?focus=1706.03815","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}