Slovenian End-to-End Automatic Speech Recognition and the Impact of Emotional Speech

Emotions are a vital component of human interaction and can impact the performance of speech technologies such as automatic speech recognition significantly. Therefore, this paper analyzes how emotional speech affects the correctness of the Slovenian end-to-end automatic speech recognizer. The open-data Slovenian Artur speech database was employed as the speech resource for training the speech recognizer, and the Slovenian part of the Interface emotional speech database was used to analyze the impact of emotions. The emotion test set contains 4,960 recordings, totalling 6.25 hours, and comprises six emotions and neutral speech. First, we performed a baseline evaluation of the end-to-end speech recognizer on the Artur speech database test set. The word error rate was 6.69%. The end-to-end speech recognizer was evaluated on the Interface speech database neutral emotion, achieving 33.62% WER. Then, the emotional speech was recognized. The word error rate for emotional speech increased between 35.36% and 40.02%.