{"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/lip2audspec-speech-reconstruction-from-silent","title":"Lip2AudSpec: Speech reconstruction from silent lip movements video","arxiv_id":"1710.09798","date":"2017-10-26","proceeding":null,"authors":["Hassan Akbari","Himani Arora","Liangliang Cao","Nima Mesgarani"],"abstract":"In this study, we propose a deep neural network for reconstructing\nintelligible speech from silent lip movement videos. We use auditory\nspectrogram as spectral representation of speech and its corresponding sound\ngeneration method resulting in a more natural sounding reconstructed speech.\nOur proposed network consists of an autoencoder to extract bottleneck features\nfrom the auditory spectrogram which is then used as target to our main lip\nreading network comprising of CNN, LSTM and fully connected layers. Our\nexperiments show that the autoencoder is able to reconstruct the original\nauditory spectrogram with a 98% correlation and also improves the quality of\nreconstructed speech from the main lip reading network. Our model, trained\njointly on different speakers is able to extract individual speaker\ncharacteristics and gives promising results of reconstructing intelligible\nspeech with superior word recognition accuracy.","url_abs":"http://arxiv.org/abs/1710.09798v1","url_pdf":"http://arxiv.org/pdf/1710.09798v1.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":"lip2audspec-speech-reconstruction-from-silent","repo_url":"https://github.com/hassanhub/LipReading","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"lip-reading","task_name":"Lip Reading"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.09798","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1710.09798"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/hassanhub/LipReading","reach":null}],"summary":{"ran_fixture":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"5ae4476bec0fc995","entry":"data_augmentation","repo":"hassanhub/LipReading","repo_kind":"official","path":"codes/train_main.py","file_url":"https://github.com/hassanhub/LipReading/blob/HEAD/codes/train_main.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5ae4476bec0fc995"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}