Speech processing for under-resourced languages is an active field of research, which has
experienced significant progress during the past decade. We propose, in this paper, a …

With the emergence of deep learning, the performance of automatic speech recognition
(ASR) systems has remarkably improved. Especially for resource-rich languages such as …

Recently there has been increased interest in Automatic Speech Recognition (ASR) and
Key Word Spotting (KWS) systems for low resource languages. One of the driving forces for …

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model
training problematic for most existing languages, including languages that do not even have …

Statistics of pauses appearing in Polish as a potential source of biometry information for
automatic speaker recognition were described. The usage of three main types of acoustic …

For many languages in the world, not enough (annotated) speech data is available to train
an ASR system. We here propose a new three-step method to build an ASR system for such …

Only a handful of the world's languages are abundant with the resources that enable
practical applications of speech processing technologies. One of the methods to overcome …

We summarize the accomplishments of a multi-disciplinary workshop exploring the
computational and scientific issues surrounding the discovery of linguistic units (subwords …

Handwritten word recognition and spotting of low-resource scripts are difficult as sufficient
training data is not available and it is often expensive for collecting data of such scripts. This …

Developing high-performance speech processing systems for low-resource languages is
very challenging. One approach to address the lack of resources is to make use of data from …