We describe a novel way to implement subword language models in speech recognition
systems based on weighted finite state transducers, hidden Markov models, and deep …

High quality Automatic Speech Recognition (ASR) is a prerequisite for speech-based
applications and research. While state-of-the-art ASR software is freely available, the …

In the subject of pattern recognition, speech recognition is an important study topic. The
authors give a detailed assessment of voice recognition strategies for several majority …

Most end-to-end speech recognition systems model text directly as a sequence of characters
or sub-words. Current approaches to sub-word extraction only consider character sequence …

Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

Today, the vocabulary size for language models in large vocabulary speech recognition is
typically several hundreds of thousands of words. While this is already sufficient in some …

Low resource speech recognition can potentially benefit a lot from exploiting a pretrained
model such as wav2vec 2.0. These pretrained models have learned useful representations …

With the rapid development of speech assistants, adapting server-intended automatic
speech recognition (ASR) solutions to a direct device has become crucial. For on-device …

We introduce the first attempt at automatic speech recognition (ASR) in Inuktitut, as a
representative for polysynthetic, low-resource languages, like many of the 900 Indigenous …

Data-driven segmentation of words into subword units has been used in various natural
language processing applications such as automatic speech recognition and statistical …