Transformer-Based Automatic Speech Recognition of Formal and Colloquial Czech in MALACH Project

被引:2
|
作者
Lehecka, Jan [1 ]
Psutka, Josef, V [1 ]
Psutka, Josef [1 ]
机构
[1] Univ West Bohemia Pilsen, Dept Cybernet, Plzen, Czech Republic
来源
关键词
Wav2Vec; 2.0; Colloquial speech; ASR;
D O I
10.1007/978-3-031-16270-1_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Czech is a very specific language due to its large differences between the formal and the colloquial form of speech. While the formal (written) form is used mainly in official documents, literature, and public speeches, the colloquial (spoken) form is used widely among people in casual speeches. This gap introduces serious problems for ASR systems, especially when training or evaluating ASR models on datasets containing a lot of colloquial speech, such as the MALACH project. In this paper, we are addressing this problem in the light of a new paradigm in end-to-end ASR systems - recently introduced self-supervised audio Transformers. Specifically, we are investigating the influence of colloquial speech on the performance of Wav2Vec 2.0 models and their ability to transcribe colloquial speech directly into formal transcripts. We are presenting results with both formal and colloquial forms in the training transcripts, language models, and evaluation transcripts.
引用
收藏
页码:301 / 312
页数:12
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