10 citations · 16 across the 13 of their papers we have counts for
3 papers · 1 filter
Discovering Phonetic Inventories with Crosslingual Automatic Speech Recognition
Piotr Żelasko, Siyuan Feng, Laureano Moro Velazquez +5
The high cost of data acquisition makes Automatic Speech Recognition (ASR) model training problematic for most existing languages, including languages that do not even have a writt…
Lhotse: a speech data representation library for the modern deep learning ecosystem
Piotr Żelasko, Daniel Povey, Jan "Yenda" Trmal +1
Speech data is notoriously difficult to work with due to a variety of codecs, lengths of recordings, and meta-data formats. We present Lhotse, a speech data representation library…
CopyPaste: An Augmentation Method for Speech Emotion Recognition
Raghavendra Pappagari, Jesús Villalba, Piotr Żelasko +2
Data augmentation is a widely used strategy for training robust machine learning models. It partially alleviates the problem of limited data for tasks like speech emotion recogniti…