{"title":"访谈笔录中的德语方言识别","authors":"S. Malmasi, Marcos Zampieri","doi":"10.18653/v1/W17-1220","DOIUrl":null,"url":null,"abstract":"This paper presents three systems submitted to the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2017. The task consists of training models to identify the dialect of Swiss-German speech transcripts. The dialects included in the GDI dataset are Basel, Bern, Lucerne, and Zurich. The three systems we submitted are based on: a plurality ensemble, a mean probability ensemble, and a meta-classifier trained on character and word n-grams. The best results were obtained by the meta-classifier achieving 68.1% accuracy and 66.2% F1-score, ranking first among the 10 teams which participated in the GDI shared task.","PeriodicalId":167439,"journal":{"name":"Workshop on NLP for Similar Languages, Varieties and Dialects","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"German Dialect Identification in Interview Transcriptions\",\"authors\":\"S. Malmasi, Marcos Zampieri\",\"doi\":\"10.18653/v1/W17-1220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents three systems submitted to the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2017. The task consists of training models to identify the dialect of Swiss-German speech transcripts. The dialects included in the GDI dataset are Basel, Bern, Lucerne, and Zurich. The three systems we submitted are based on: a plurality ensemble, a mean probability ensemble, and a meta-classifier trained on character and word n-grams. The best results were obtained by the meta-classifier achieving 68.1% accuracy and 66.2% F1-score, ranking first among the 10 teams which participated in the GDI shared task.\",\"PeriodicalId\":167439,\"journal\":{\"name\":\"Workshop on NLP for Similar Languages, Varieties and Dialects\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on NLP for Similar Languages, Varieties and Dialects\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/W17-1220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on NLP for Similar Languages, Varieties and Dialects","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W17-1220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
German Dialect Identification in Interview Transcriptions
This paper presents three systems submitted to the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2017. The task consists of training models to identify the dialect of Swiss-German speech transcripts. The dialects included in the GDI dataset are Basel, Bern, Lucerne, and Zurich. The three systems we submitted are based on: a plurality ensemble, a mean probability ensemble, and a meta-classifier trained on character and word n-grams. The best results were obtained by the meta-classifier achieving 68.1% accuracy and 66.2% F1-score, ranking first among the 10 teams which participated in the GDI shared task.
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