3 accepted papers
Naturally introduced perturbations in audio signal, caused by emotional and physical states of the speaker, can significantly degrade the performance of Automatic Speech Recognition (ASR) systems. In this paper, we propose a front-end based on Cycle-Consistent Generative Adversarial Network (CycleGA…
Recognition of Proper Names (PNs) in speech is important for content based indexing and browsing of audio-video data. However, many PNs are Out-Of-Vocabulary (OOV) words for LVCSR systems used in these applications due to the diachronic nature of data. By exploiting semantic context of the audio, re…
Retrieving Proper Names (PNs) specific to an audio document can be useful for vocabulary selection and OOV recovery in speech recognition, as well as in keyword spotting and audio indexing tasks. We propose methods to infer and retrieve OOV PNs relevant to an audio news document by using probabilist…