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 …

This paper introduces the system ParliamentSampo–Parliament of Finland on the Semantic
Web, a Linked Open Data (LOD) service, data infrastructure, and semantic portal for …

Public sources like parliament meeting recordings and transcripts provide ever-growing
material for the training and evaluation of automatic speech recognition (ASR) systems. In …

Abstract Neural Text-to-Speech (TTS) synthesis is able to generate highquality speech with
natural prosody. However, these systems typically require a large amount of data, preferably …

This paper presents a new open infrastructure called ParliamentSampo for studying the
parliamentary culture, language, and activities of politicians in Finland. For the first time, the …

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 …

This paper presents a new infrastructure and semantic portal called ParliamentSampo for
studying parliamentary speeches, culture, language, and activities in Finland. For the first …

This paper presents our bootstrapping efforts of producing the first large freely available
Croatian automatic speech recognition (ASR) dataset, 1,816 hours in size, obtained from …

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 …

Automatic speech recognition systems require large annotated speech corpus. The manual
annotation of a large corpus is very difficult. In this paper, we focus on the automatic …