Most languages have no established writing system and minimal written records. However,
textual data is essential for natural language processing, and particularly important for …

Automatic speech recognition tools have potential for facilitating language documentation,
but in practice these tools remain little-used by linguists for a variety of reasons, such as that …

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 …

Generating accurate word-level transcripts of recorded speech for language documentation
is difficult and time-consuming, even for skilled speakers of the target language. Automatic …

In this paper, principal methods for solving training data issues for the so-called low-
resource languages are discussed, regarding elaboration of automatic speech recognition …

Automatic speech recognition (ASR) systems require large amounts of transcribed speech
data, for training state-of-the-art deep neural network (DNN) acoustic models. Transcribed …

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 …

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 …

In this article, the concept (ie, the mathematical model and methods) of computational
phonetic analysis of speech with an analytical description of the phenomenon of phonetic …

В статье рассматриваются основные методы решения проблемы малых наборов
обучающих данных для создания автоматических систем распознавания речи для так …