Spoken term detection (STD) provides an efficient means for content based indexing of
speech. However, achieving high detection performance, faster speed, detecting ot-of …

In the conventional frame feature based music genre classification methods, the audio data
is represented by independent frames and the sequential nature of audio is totally ignored. If …

State-of-the-art query-by-example (QbE) speech search approaches usually use recurrent
neural network (RNN) based acoustic word embeddings (AWEs) to represent variable …

Acoustic word embeddings (AWEs) have been popular in low-resource query-by-example
speech search. They are using vector distances to find the spoken query in search content …

Folk music style classification is of great significance. Traditional folk music style
classification has difficulties in feature selection, and the existing folk music style methods …

Mobile devices are widely used around the world, frequently by people speaking local
languages or dialects that are not well documented. For these languages, it might not be …

In this paper, we aim to automatically discover high-quality frame-level speech features and
acoustic tokens directly from unlabeled speech data. A multigranular acoustic tokenizer …

Zerospeech synthesis is the task of building vocabulary independent speech synthesis
systems, where transcriptions are not available for training data. It is, therefore, necessary to …

Acoustic modelling in the absence of labelled audio is difficult in speech processing,
especially in under-resourced languages. Ideas from theories of speech production and …

Unsupervised discovery of sub-lexical units in speech is a problem that currently interests
speech researchers. In this paper, we report experiments in which we use phone …