Recently, the speech community is seeing a significant trend of moving from deep neural
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …

Code-switching is a speech phenomenon occurring when a speaker switches language
during a conversation. Despite the spontaneous nature of code-switching in conversational …

We investigate using large language models (LLMs) to generate text-only training data for
improving multilingual and code-switching automatic speech recognition (ASR) through a …

In this paper, a semisupervised speech data extraction method is presented and applied to
create a new dataset designed for the development of fully bilingual Automatic Speech …

In Uyghur speech, consonant and vowel reduction are often encountered, especially in
spontaneous speech with high speech rate, which will cause a degradation of speech …

Recognizing code-switching (CS) speech often presents challenges for an automatic
speech recognition system (ASR) due to limited linguistic context in short monolingual …

Code-switching describes the practice of using more than one language in the same
sentence. In this study, we investigate how to optimize a neural transducer based bilingual …

In this paper, we investigate how the output representation of an end-to-end neural network
affects multilingual automatic speech recognition (ASR). We study different representations …

Connectionist Temporal Classification (CTC) loss has become widely used in sequence
modeling tasks such as Automatic Speech Recognition (ASR) and Handwritten Text …

Automatic speech recognition (ASR) of speech signals with code-switching (an abrupt
language change common in bilingual communities) typically requires spoken language …