{"id":26248,"date":"2024-02-25T06:27:29","date_gmt":"2024-02-25T07:27:29","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%d9%85%d9%82%d8%a7%d9%84%d9%87-%d8%aa%d9%86%d8%b8%db%8c%d9%85-%d8%af%d9%82%db%8c%d9%82-%d8%a2%d8%af%d8%a7%d9%be%d8%aa%d9%88%d8%b1-%da%a9%d8%a7%d8%b1%d8%a2%d9%85%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d8%b2\/"},"modified":"2024-02-25T06:27:30","modified_gmt":"2024-02-25T07:27:30","slug":"%d9%85%d9%82%d8%a7%d9%84%d9%87-%d8%aa%d9%86%d8%b8%db%8c%d9%85-%d8%af%d9%82%db%8c%d9%82-%d8%a2%d8%af%d8%a7%d9%be%d8%aa%d9%88%d8%b1-%da%a9%d8%a7%d8%b1%d8%a2%d9%85%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d8%b2","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d9%85%d9%82%d8%a7%d9%84%d9%87-%d8%aa%d9%86%d8%b8%db%8c%d9%85-%d8%af%d9%82%db%8c%d9%82-%d8%a2%d8%af%d8%a7%d9%be%d8%aa%d9%88%d8%b1-%da%a9%d8%a7%d8%b1%d8%a2%d9%85%d8%af-%d8%a8%d8%b1%d8%a7%db%8c-%d8%b2\/","title":{"rendered":"\u0645\u0642\u0627\u0644\u0647 \u062a\u0646\u0638\u06cc\u0645 \u062f\u0642\u06cc\u0642 \u0622\u062f\u0627\u067e\u062a\u0648\u0631 \u06a9\u0627\u0631\u0622\u0645\u062f \u0628\u0631\u0627\u06cc \u0632\u0628\u0627\u0646 \u0647\u0627\u06cc \u062f\u0646\u0628\u0627\u0644\u0647 \u062f\u0631 \u067e\u062e\u0634 \u062c\u0631\u06cc\u0627\u0646\u06cc ASR \u0686\u0646\u062f \u0632\u0628\u0627\u0646\u0647"},"content":{"rendered":"<table class=\"table table-striped table-hover\">\n<tbody>\n<tr>\n<td>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\n<td>Efficient Adapter Finetuning for Tail Languages in Streaming Multilingual ASR<\/td>\n<\/tr>\n<tr>\n<td>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n<td>\u0645\u0642\u0627\u0644\u0647 \u0622\u062f\u0627\u067e\u062a\u0648\u0631 \u06a9\u0627\u0631\u0622\u0645\u062f \u0628\u0631\u0627\u06cc \u0632\u0628\u0627\u0646\u0647\u0627\u06cc \u062f\u0645 \u062f\u0631 \u062c\u0631\u06cc\u0627\u0646 ASR \u0686\u0646\u062f \u0632\u0628\u0627\u0646\u0647<\/td>\n<\/tr>\n<tr>\n<td>\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\n<td>Junwen Bai, Bo Li, Qiujia Li, Tara N. Sainath, Trevor Strohman<\/td>\n<\/tr>\n<tr>\n<td>\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 <\/td>\n<td>\u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n<\/tr>\n<tr>\n<td>\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647: <\/td>\n<td>PDF<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n<td>5<\/td>\n<\/tr>\n<tr>\n<td>\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a  <\/td>\n<td>Computation and Language,Machine Learning,Sound,Audio and Speech Processing,\u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0648 \u0632\u0628\u0627\u0646 , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 , \u0635\u062f\u0627 , \u0635\u062f\u0627 \u0648 \u06af\u0641\u062a\u0627\u0631 ,<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a    <\/td>\n<td>Submitted 17 January, 2024; originally announced January 2024. , Comments: Accepted to ICASSP 2024<\/td>\n<\/tr>\n<tr>\n<td>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc    <\/td>\n<td>\u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 17 \u0698\u0627\u0646\u0648\u06cc\u0647 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0698\u0627\u0646\u0648\u06cc\u0647 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f \u060c \u0646\u0638\u0631\u0627\u062a: \u067e\u0630\u06cc\u0631\u0641\u062a\u0647 \u0634\u062f\u0647 \u0628\u0631\u0627\u06cc ICASSP 2024<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n<p style=\"direction:ltr;\">The end-to-end ASR model is often desired in the streaming multilingual scenario since it is easier to deploy and can benefit from pre-trained speech models such as powerful foundation models. Meanwhile, the heterogeneous nature and imbalanced data abundance of different languages may cause performance degradation, leading to asynchronous peak performance for different languages during training, especially on tail ones. Sometimes even the data itself may become unavailable as a result of the enhanced privacy protection. Existing work tend to significantly increase the model size or learn language-specific decoders to accommodate each language separately. In this study, we explore simple yet effective Language-Dependent Adapter (LDA) finetuning under a cascaded Conformer transducer framework enhanced by teacher pseudo-labeling for tail languages in the streaming multilingual ASR. The adapter only accounts for 0.4% of the full model per language. It is plugged into the frozen foundation model and is the only trainable module during the finetuning process with noisy student training. The final model merges the adapter parameters from different checkpoints for different languages. The model performance is validated on a challenging multilingual dictation dataset, which includes 39 tail languages across Latin, Greek, Arabic, etc. Our proposed method brings 12.2% word error rate reduction on average and up to 37.5% on a single locale. Furthermore, we show that our parameter-efficient LDA can match the quality of the full model finetuning, thus greatly alleviating the asynchronous peak performance issue.<\/p>\n<h2>\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n<p>\u0645\u062f\u0644 ASR \u067e\u0627\u06cc\u0627\u0646 \u0628\u0647 \u067e\u0627\u06cc\u0627\u0646 \u0627\u063a\u0644\u0628 \u062f\u0631 \u0633\u0646\u0627\u0631\u06cc\u0648\u06cc \u0686\u0646\u062f \u0632\u0628\u0627\u0646\u0647 \u062c\u0631\u06cc\u0627\u0646 \u0645\u0648\u0631\u062f \u0646\u0638\u0631 \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0622\u0646 \u0622\u0633\u0627\u0646 \u062a\u0631 \u0627\u0633\u062a \u0648 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0627\u0632 \u0645\u062f\u0644\u0647\u0627\u06cc \u06af\u0641\u062a\u0627\u0631 \u0627\u0632 \u067e\u06cc\u0634 \u0622\u0645\u0648\u0632\u0634 \u062f\u06cc\u062f\u0647 \u0645\u0627\u0646\u0646\u062f \u0645\u062f\u0644\u0647\u0627\u06cc \u0628\u0646\u06cc\u0627\u062f\u06cc \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0628\u0647\u0631\u0647 \u0645\u0646\u062f \u0634\u0648\u062f.\u062f\u0631 \u0647\u0645\u06cc\u0646 \u062d\u0627\u0644 \u060c \u0645\u0627\u0647\u06cc\u062a \u0646\u0627\u0647\u0645\u06af\u0646 \u0648 \u0641\u0631\u0627\u0648\u0627\u0646\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0646\u0627\u0645\u062a\u0639\u0627\u062f\u0644 \u0627\u0632 \u0632\u0628\u0627\u0646\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u0627\u0639\u062b \u062a\u062e\u0631\u06cc\u0628 \u0639\u0645\u0644\u06a9\u0631\u062f \u0634\u0648\u062f \u0648 \u0645\u0646\u062c\u0631 \u0628\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0648\u062c \u0646\u0627\u0647\u0645\u0632\u0645\u0627\u0646 \u0628\u0631\u0627\u06cc \u0632\u0628\u0627\u0646\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u062f\u0631 \u0637\u0648\u0644 \u0622\u0645\u0648\u0632\u0634 \u060c \u0628\u0647 \u0648\u06cc\u0698\u0647 \u062f\u0631 \u0645\u0648\u0631\u062f \u062f\u0645 \u0634\u0648\u062f.\u06af\u0627\u0647\u06cc \u0627\u0648\u0642\u0627\u062a \u062d\u062a\u06cc \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0645\u062d\u0627\u0641\u0638\u062a \u0627\u0632 \u062d\u0631\u06cc\u0645 \u062e\u0635\u0648\u0635\u06cc \u0627\u0641\u0632\u0627\u06cc\u0634 \u06cc\u0627\u0641\u062a\u0647 \u062f\u0631 \u062f\u0633\u062a\u0631\u0633 \u0646\u0628\u0627\u0634\u0646\u062f.\u06a9\u0627\u0631 \u0645\u0648\u062c\u0648\u062f \u062a\u0645\u0627\u06cc\u0644 \u062f\u0627\u0631\u062f \u0627\u0646\u062f\u0627\u0632\u0647 \u0645\u062f\u0644 \u0631\u0627 \u0628\u0647 \u0637\u0648\u0631 \u0642\u0627\u0628\u0644 \u062a\u0648\u062c\u0647\u06cc \u0627\u0641\u0632\u0627\u06cc\u0634 \u062f\u0647\u062f \u06cc\u0627 \u0631\u0645\u0632\u06af\u0634\u0627\u0647\u0627\u06cc \u062e\u0627\u0635 \u0632\u0628\u0627\u0646 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0633\u06a9\u0627\u0646 \u0647\u0631 \u0632\u0628\u0627\u0646 \u0628\u0647 \u0637\u0648\u0631 \u062c\u062f\u0627\u06af\u0627\u0646\u0647 \u06cc\u0627\u062f \u0628\u06af\u06cc\u0631\u062f.\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u060c \u0645\u0627 \u0628\u0647 \u0628\u0631\u0631\u0633\u06cc \u0622\u062f\u0627\u067e\u062a\u0648\u0631 \u0633\u0627\u062f\u0647 \u0648 \u062f\u0631 \u0639\u06cc\u0646 \u062d\u0627\u0644 \u0645\u0624\u062b\u0631 \u0648\u0627\u0628\u0633\u062a\u0647 \u0628\u0647 \u0632\u0628\u0627\u0646 (LDA) \u062f\u0631 \u0632\u06cc\u0631 \u06cc\u06a9 \u0686\u0627\u0631\u0686\u0648\u0628 \u0645\u0628\u062f\u0644 \u0633\u0627\u0632\u0646\u062f\u0647 \u0622\u0628\u0634\u0627\u0631 \u06a9\u0647 \u062a\u0648\u0633\u0637 \u0645\u0639\u0644\u0645 \u0634\u0628\u0647 \u0628\u0631\u0686\u0633\u0628 \u0632\u062f\u0646 \u0628\u0631\u0627\u06cc \u0632\u0628\u0627\u0646\u0647\u0627\u06cc \u062f\u0645 \u062f\u0631 \u062c\u0631\u06cc\u0627\u0646 \u0686\u0646\u062f \u0632\u0628\u0627\u0646\u0647 ASR \u062a\u0642\u0648\u06cc\u062a \u0634\u062f\u0647 \u0627\u0633\u062a \u060c \u06a9\u0634\u0641 \u0645\u06cc \u06a9\u0646\u06cc\u0645.\u0622\u062f\u0627\u067e\u062a\u0648\u0631 \u0641\u0642\u0637 0.4 \u066a \u0627\u0632 \u0645\u062f\u0644 \u06a9\u0627\u0645\u0644 \u0631\u0627 \u062f\u0631 \u0647\u0631 \u0632\u0628\u0627\u0646 \u062a\u0634\u06a9\u06cc\u0644 \u0645\u06cc \u062f\u0647\u062f.\u0627\u06cc\u0646 \u0645\u062f\u0644 \u0628\u0647 \u0645\u062f\u0644 \u0628\u0646\u06cc\u0627\u062f \u0645\u0646\u062c\u0645\u062f \u0648\u0635\u0644 \u0634\u062f\u0647 \u0648 \u062a\u0646\u0647\u0627 \u0645\u0627\u0698\u0648\u0644 \u0642\u0627\u0628\u0644 \u0622\u0645\u0648\u0632\u0634 \u062f\u0631 \u0637\u06cc \u0641\u0631\u0622\u06cc\u0646\u062f FinetUning \u0628\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u0646\u0634\u062c\u0648\u06cc\u06cc \u067e\u0631 \u0633\u0631 \u0648 \u0635\u062f\u0627 \u0627\u0633\u062a.\u0645\u062f\u0644 \u0646\u0647\u0627\u06cc\u06cc \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0622\u062f\u0627\u067e\u062a\u0648\u0631 \u0631\u0627 \u0627\u0632 \u067e\u0627\u0633\u06af\u0627\u0647 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0628\u0631\u0627\u06cc \u0632\u0628\u0627\u0646\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0627\u062f\u063a\u0627\u0645 \u0645\u06cc \u06a9\u0646\u062f.\u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062f\u0644 \u062f\u0631 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062f\u06cc\u06a9\u062a\u0647 \u0686\u0646\u062f \u0632\u0628\u0627\u0646\u0647 \u0686\u0627\u0644\u0634 \u0628\u0631\u0627\u0646\u06af\u06cc\u0632 \u060c \u06a9\u0647 \u0634\u0627\u0645\u0644 39 \u0632\u0628\u0627\u0646 \u062f\u0645 \u062f\u0631 \u0633\u0631\u0627\u0633\u0631 \u0644\u0627\u062a\u06cc\u0646 \u060c \u06cc\u0648\u0646\u0627\u0646\u06cc \u060c \u0639\u0631\u0628\u06cc \u0648 \u063a\u06cc\u0631\u0647 \u0627\u0633\u062a \u060c \u062a\u0623\u06cc\u06cc\u062f \u0645\u06cc \u0634\u0648\u062f.\u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646 \u060c \u0645\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u06cc\u0645 \u06a9\u0647 LDA \u0628\u0627 \u06a9\u0627\u0631\u0622\u0645\u062f \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0627 \u06a9\u06cc\u0641\u06cc\u062a \u0645\u062f\u0644 \u06a9\u0627\u0645\u0644 Finetuning \u0645\u0637\u0627\u0628\u0642\u062a \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f \u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0645\u0633\u0626\u0644\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0648\u062c \u0646\u0627\u0647\u0645\u0632\u0645\u0627\u0646 \u0631\u0627 \u062a\u0627 \u062d\u062f \u0632\u06cc\u0627\u062f\u06cc \u06a9\u0627\u0647\u0634 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n<table class=\"table table-bordered table-primary\">\r\n<tr>\r\n\t<td>\r\n\t\u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u0627\u0633\u062a.\r\n\t<\/td>\r\n<\/tr>\r\n\t\r\n<tr>\r\n\t<td>\r\n     \u0628\u0631\u0627\u06cc \u0633\u0641\u0627\u0631\u0634 \u062a\u0631\u062c\u0645\u0647 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u06cc\u06a9\u06cc \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0645\u0627\u0633\u060c \u067e\u06cc\u0627\u0645\u06a9\u060c \u062a\u0644\u06af\u0631\u0627\u0645 \u0648 \u06cc\u0627 \u0648\u0627\u062a\u0633 \u0627\u067e \u0628\u0627 \u0634\u0645\u0627\u0631\u0647 \u0632\u06cc\u0631 \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f:\r\n\t<br \/><br \/>\r\n\t09395106248\r\n\t\t\r\n\t\t\r\n\t<br \/><br \/>\r\n\t\t\u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0634\u0631\u0627\u06cc\u0637 \u062a\u0631\u062c\u0645\u0647 \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u0627\u0633\u062a:\r\n\t\t<br \/>\r\n\t\t<ul>\r\n\t\t<li>\r\n\t\t\u0642\u06cc\u0645\u062a \u0647\u0631 \u0635\u0641\u062d\u0647 \u062a\u0631\u062c\u0645\u0647 \u062f\u0631 \u062d\u0627\u0644 \u062d\u0627\u0636\u0631 40 \u0647\u0632\u0627\u0631 \u062a\u0648\u0645\u0627\u0646 \u0645\u06cc \u0628\u0627\u0634\u062f. \r\n\t\t<\/li>\r\n\t\t<li>\r\n\t\t\u062a\u062d\u0648\u06cc\u0644 \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f \u0645\u06cc \u0628\u0627\u0634\u062f.\r\n\t\t<\/li>\r\n\t\t<li>\r\n\t\t\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u0635\u0648\u0631\u062a \u062f\u0627\u0634\u062a\u0646 \u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a \u0639\u0627\u062f\u06cc \u0628\u06cc\u0646 3 \u062a\u0627 5 \u0631\u0648\u0632 \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f.\r\n\t\t<\/li>\r\n\t\t\r\n\t\t<li>\r\n\t\t\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627 \u0645\u06cc \u0628\u0627\u0634\u062f. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.\r\n\t\t<\/li>\r\n\t\t<li>\r\n\t\t\u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.\r\n\t\t<\/li>\r\n\t<\/td>\r\n\t\r\n\t\r\n<\/tr>\r\n<\/table>\r\n\r\n\r\n\n","protected":false},"excerpt":{"rendered":"<p>\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc Efficient Adapter Finetuning for Tail Languages in Streaming Multilingual ASR \u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u0622\u062f\u0627\u067e\u062a\u0648\u0631 [&hellip;]<\/p>\n","protected":false},"featured_media":27,"comment_status":"open","ping_status":"closed","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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