{"doi":"10.4018/9781605661865.ch011","title":"Hidden Markov Model Based Visemes Recognition, Part I","abstract":"<jats:p>Visual speech recognition is able to supplement the information of speech sound to improve the accuracy of speech recognition. A viseme, which describes the facial and oral movements that occur alongside the voicing of a particular phoneme, is a supposed basic unit of speech in the visual domain. As in phonemes, there are variations for the same viseme expressed by different persons or even by the same person. A classifier must be robust to this kind of variation. In this chapter, the author’s describe the Adaptively Boosted (AdaBoost) Hidden Markov Model (HMM) technique (Foo, 2004; Foo, 2003; Dong, 2002). By applying the AdaBoost technique to HMM modeling, a multi-HMM classifier that improves the robustness of HMM is obtained. The method is applied to identify context-independent and contextdependent visual speech units. Experimental results indicate that higher recognition accuracy can be attained using the AdaBoost HMM than that using conventional HMM.</jats:p>","journal":null,"year":null,"id":683591,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Hidden Markov Model Based Visemes Recognition, Part I","abstract":"<jats:p>Visual speech recognition is able to supplement the information of speech sound to improve the accuracy of speech recognition. A viseme, which describes the facial and oral movements that occur alongside the voicing of a particular phoneme, is a supposed basic unit of speech in the visual domain. As in phonemes, there are variations for the same viseme expressed by different persons or even by the same person. A classifier must be robust to this kind of variation. In this chapter, the author’s describe the Adaptively Boosted (AdaBoost) Hidden Markov Model (HMM) technique (Foo, 2004; Foo, 2003; Dong, 2002). By applying the AdaBoost technique to HMM modeling, a multi-HMM classifier that improves the robustness of HMM is obtained. The method is applied to identify context-independent and contextdependent visual speech units. Experimental results indicate that higher recognition accuracy can be attained using the AdaBoost HMM than that using conventional HMM.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26207759","pmcid":null,"openalex_id":"https://openalex.org/W4253235840","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.47606918,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://www.igi-global.com/viewtitle.aspx?TitleId=31073","host_type":"publisher"},{"url":"https://doi.org/10.4018/9781605661865.ch011","host_type":"ebook platform"}],"fields_of_study":["Video Surveillance and Tracking Methods","Face and Expression Recognition","Text and Document Classification Technologies"],"mesh_terms":[],"keywords":["Hidden Markov model","Computer science","Speech recognition","Viseme","Markov model","Artificial intelligence","Pattern recognition (psychology)","Markov chain","Machine learning","Acoustic model","Speech processing"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Quality Education"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-18T11:36:21.647081Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}