With recent advances in machine-learning techniques for automatic speech analysis (ASA)-
the computerized extraction of information from speech signals-there is a greater need for …

Spoken content retrieval refers to directly indexing and retrieving spoken content based on
the audio rather than text descriptions. This potentially eliminates the requirement of …

In the last years, the task of Query-by-Example Spoken Term Detection (QbE-STD), which
aims to find occurrences of a spoken query in a set of audio documents, has gained the …

This paper presents a study of spectral clustering-based approaches to acoustic segment
modeling (ASM). ASM aims at finding the underlying phoneme-like speech units and …

In this paper, we describe the “Spoken Web Search” Task, which was held as part of the
2012 MediaEval benchmark evaluation campaign. The purpose of this task was to perform …

We propose a framework which ports Dirichlet Gaussian mixture model (DPGMM) based
labels to deep neural network (DNN). The DNN trained using the unsupervised labels is …

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 …

In this paper, we describe several approaches to language-independent spoken term
detection and compare their performance on a common task, namely “Spoken Web Search” …

The combination of several heterogeneous systems is known to provide remarkable
performance improvements in verification and detection tasks. In Spoken Term Detection …

In the present research, we tackle the problem of query by example spoken term detection
(QbE-STD) in the zero-resource scenario. State-of-the-art methods typically use dynamic …