{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11257481","patent":{"patent_number":"US-11257481","title":"Multi-task training architecture and strategy for attention-based speech recognition system","assignee":null,"inventors":[],"filing_date":"2018-10-24T00:00:00.000Z","publication_date":"2022-02-22T00:00:00.000Z","cpc_codes":["G10L","G10L","G10L","G10L","G10L"],"num_claims":20,"abstract":"Methods and apparatuses are provided for performing sequence to sequence (Seq2Seq) speech recognition training performed by at least one processor. The method includes acquiring a training set comprising a plurality of pairs of input data and target data corresponding to the input data, encoding the input data into a sequence of hidden states, performing a connectionist temporal classification (CTC) model training based on the sequence of hidden states, performing an attention model training based on the sequence of hidden states, and decoding the sequence of hidden states to generate target labels by independently performing the CTC model training and the attention model training."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Multi-task training architecture and strategy for attention-based speech recognition system","description":"Methods and apparatuses are provided for performing sequence to sequence (Seq2Seq) speech recognition training performed by at least one processor. The method includes acquiring a training set compris","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11257481","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11257481","citation_suggestion":"Patentable. \"Multi-task training architecture and strategy for attention-based speech recognition system\" (US-11257481). https://patentable.app/patents/US-11257481","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11257481","json":"https://patentable.app/api/llm-context/US-11257481","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T18:03:05.119Z"}