| Autor: |
Li Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Systems and Soft Computing, Vol 6, Iss , Pp 200131- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2772-9419 |
| DOI: |
10.1016/j.sasc.2024.200131 |
| Popis: |
In order to improve English learning efficiency, this paper constructs a deep learning model of semantic orientation exploration based on English V+able corpus distribution and semantic roles. This article combines the practical needs of English learning and establishes an ILP model with the optimization objective of minimizing spectrum resource occupation. A traffic grooming based time aware multipath RSA algorithm (HMRSA-TG) is proposed to solve the standardization problem of English speech recognition. To improve the system efficiency of intelligent English learning systems, a traffic grooming based time aware multipath RSA algorithm (HMRSA-TG) is proposed. Through research, it has been verified that the semantic orientation exploration deep learning model based on the distribution of semantic roles in English V+able corpora can effectively improve the effectiveness of English speech learning. The corpus model proposed in this paper can provide a reliable benchmark database for many speech problem learners and play an important role in English translation software in recognizing input speech with different accents |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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