A novel keyword rescoring method for improved spoken keyword spotting

Spoken keyword spotting via multi-lattice alignment

We propose a method for finding keywords in an audio database using a spoken query. Our method is based on performing a joint alignment between a phone lattice generated from a spoken utterance query and a second phone lattice representing a long utterance needing to be searched. We implement this joint alignment procedure in a graphical models framework. We evaluate our system on TIMIT as well...

Comparing Different Word Lattice Rescoring Approaches Towards Keyword Spotting

Spoken Keyword Rescoring and Document Retrieval for Low-resource Languages

For languages that have adequate data for automatic speech recognition (ASR), many keyword search(KWS) and document retrieval(SDR) systems have been developed with near-optimal performance. However, lacking of sufficient training data to produce high accuracy transcript, identification and retrieval of queries in speech data from low-resources languages remains challenging. To compensate for th...

Low Resource Keyword Spotting

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...