A study argues that one-shot magnitude pruning does more than compress neural networks, acting as an implicit regularizer for automatic speech recognition. Testing with Whisper-small, the authors combine gradient- and Fisher-based sensitivity measures to guide which weights to remove. The work reframes pruning as a training technique rather than only a efficiency tool.
Researchers have released BaltiVoice, a 16.8-hour read-speech corpus with 10,060 validated utterances for Balti, a Tibetic language spoken in Gilgit-Baltistan, Pakistan. The language previously had no publicly available speech recognition resources, making this the first open dataset and ASR model for Balti. The team fine-tuned OpenAI's Whisper architecture on the corpus to enable automatic speech recognition for the language.
A new arXiv paper introduces BuzzASR, a collection of more than one hundred monolingual Whisper models fine-tuned for automatic speech recognition in 102 languages. The language-specialized models are designed to cover languages that large general-purpose multilingual ASR systems often serve poorly. The release is presented as a resource for practitioners and researchers working on speech technology across many languages.