55 citations · 85 across the 19 of their papers we have counts for
10 papers · 1 filter
As Biased as You Measure: Methodological Pitfalls of Bias Evaluations in Speaker Verification Research
Wiebke Hutiri, Tanvina Patel, Aaron Yi Ding +1
Detecting and mitigating bias in speaker verification systems is important, as datasets, processing choices and algorithms can lead to performance differences that systematically f…
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…
Improving Whispered Speech Recognition Performance using Pseudo-whispered based Data Augmentation
Zhaofeng Lin, Tanvina Patel, Odette Scharenborg
Whispering is a distinct form of speech known for its soft, breathy, and hushed characteristics, often used for private communication. The acoustic characteristics of whispered spe…
The Multimodal Information Based Speech Processing (MISP) 2023 Challenge: Audio-Visual Target Speaker Extraction
Shilong Wu, Chenxi Wang, Hang Chen +13
Previous Multimodal Information based Speech Processing (MISP) challenges mainly focused on audio-visual speech recognition (AVSR) with commendable success. However, the most advan…
Unsupervised Acoustic Unit Discovery by Leveraging a Language-Independent Subword Discriminative Feature Representation
Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +1
This paper tackles automatically discovering phone-like acoustic units (AUD) from unlabeled speech data. Past studies usually proposed single-step approaches. We propose a two-stag…
Quantifying Bias in Automatic Speech Recognition
Siyuan Feng, Olya Kudina, Bence Mark Halpern +1
Automatic speech recognition (ASR) systems promise to deliver objective interpretation of human speech. Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs…