Keyword Spotting in Multilingual Environments

Discriminative keyword spotting

This paper proposes a new approach for keyword spotting, which is not based on HMMs. The proposed method employs a new discriminative learning procedure, in which the learning phase aims at maximizing the area under the ROC curve, as this quantity is the most common measure to evaluate keyword spotters. The keyword spotter we devise is based on nonlinearly mapping the input acoustic representat...

Low Resource Keyword Spotting

Keyword Spotting Using Durational Entropy

This paper deals with the task of detection of a given keyword in continuous speech. We build upon a previously proposed algorithm where a modified Viterbi search algorithm is used to detect keywords, without requiring any explicit garbage or filler models. In this work, the concept of durational entropy is used to further discard a large fraction of false alarm errors. Durational entropy is de...

Morphological Segmentation for Keyword Spotting

• We explore the impact of morphological segmentation on Keyword Spotting (KWS). ! • Handling out-of-vocabulary (OOV) words is a major challenge in KWS we aim to alleviate this problem by utilizing sub-word units.! • We augment a state-of-the-art KWS system with subword units derived from supervised and unsupervised morphological segmentations, and compare with phonetic and syllabic segmentatio...

Document Image Retrieval Based on Keyword Spotting Using Relevance Feedback

Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...