Performance Improvement in Keyword Spotting for Telephony Services

Performance Improvement in Keyword Spotting for Telephony Services

In this paper, a new hybrid approach is presented for keyword spotting. The proposed Method is based on Hidden Markov Mode (HMM) and is performed in two stages. In the first stage by using phoneme models, a series of candidate keyword(s) is recognized. In the second stage, word models are used to decide on acceptance or rejection of each candidate keyword. Two different methods are presented in...

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...

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

Performance Evaluation of Non-Keyword Modeling for Vocabulary-Independent Keyword Spotting

In this paper, we develop a keyword spotting system using vocabulary-independent speech recognition technique, and investigate several non-keyword modeling methods to improve its performance. In order to overcome the weakness of conventional syllable model, we propose the syllable filler based on syllable information of keywords and syllable-like filler model. The former prohibits syllable fill...