4 accepted papers
Multilingual speech recognition systems often use an input language code in order to prompt the transcription in the target language. However, the spoken language in the input audio may not always match the language code, as often prevalent in multilingual societies. This language mismatch can signi…
The state-of-the-art conformer used in automatic speech recognition combines feed-forward, convolution and multi-headed self-attention layers in a single model that is trained end-to-end with a decoder network. While this end-to-end training is simple and beneficial for word error rate, it restricts…
The development of end-to-end models has largely sped up the research in massively multilingual automatic speech recognition (MMASR). Previous research has demonstrated the feasibility to build high quality MMASR models. In this work, we study the impact of adding more languages and propose a lifelo…
When trained on related or low-resource languages, multilingual speech recognition models often outperform their monolingual counterparts. However, these models can suffer from loss in performance for high resource or unrelated languages. We investigate the use of a mixture-of-experts approach to as…