6 citations · 6 across the 5 of their papers we have counts for
5 papers
Benchmarking Human and Automatic Speech Recognition of Diverse Speech: Initial Results
Ilse Huisman, Rares Popa, Yuanyuan Zhang +1
Humans are often considered to be the best listeners and seen as the upper-bound performance of automatic speech recognition (ASR) systems. We present a preliminary comparison of t…
Comparing Human and Automatic Recognition of Dutch Dysarthric Continuous Speech: A Case Study
Yuanyuan Zhang, Dimme de Groot, Jorge Martinez +1
In our goal to develop personalised dysarthric speech recognition (DSR) models, this study compared the recognition performances of human listeners and those of three state-of-the-…
A Semi-spontaneous Dutch Speech Dataset for Speech Enhancement and Speech Recognition
Dimme de Groot, Yuanyuan Zhang, Jorge Martinez +1
We present DRES: a 1.5-hour Dutch realistic elicited (semi-spontaneous) speech dataset from 80 speakers recorded in noisy, public indoor environments. DRES was designed as a test s…
Improving child speech recognition with augmented child-like speech
Yuanyuan Zhang, Zhengjun Yue, Tanvina Patel +1
State-of-the-art ASRs show suboptimal performance for child speech. The scarcity of child speech limits the development of child speech recognition (CSR). Therefore, we studied chi…
Exploring data augmentation in bias mitigation against non-native-accented speech
Yuanyuan Zhang, Aaricia Herygers, Tanvina Patel +2
Automatic speech recognition (ASR) should serve every speaker, not only the majority ``standard'' speakers of a language. In order to build inclusive ASR, mitigating the bias again…