There is growing interest in building phone recognition systems for low-resource languages
as the majority of languages do not have any writing systems. Phone recognition systems …

This paper proposes Allophant, a multilingual phoneme recognizer. It requires only a
phoneme inventory for cross-lingual transfer to a target language, allowing for low-resource …

In this project, we demonstrate that phoneme-based models for speech processing can
achieve strong crosslinguistic generalizability to unseen languages. We curated the …

Low-resource speech recognition has been long-suffering from insufficient training data. In
this paper, we propose an approach that leverages neighboring languages to improve low …

Identifying phone inventories is a crucial component in language documentation and the
preservation of endangered languages. However, even the largest collection of phone …

Curating datasets that span multiple languages is challenging. To make the collection more
scalable, researchers often incorporate one or more imperfect classifiers in the process, like …

In this paper, we introduce a massively multilingual speech corpora with fine-grained
phonemic transcriptions, encompassing more than 115 languages from diverse language …

Recently, the performance of speech recognition has witnessed rapid improvement due to
modern architectures. Those models typically require thousands of hours of training data for …

There is growing interest in ASR systems that can recognize phones in a language-
independent fashion. There is additionally interest in building language technologies for low …

Nigerian native languages can still be classified as under-resourced concerning the text and
speech resources required for technology development. This limitation strikes all human …