Privacy-Sensitive Audio Features for Conversational Speech Processing
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This paper investigates robust privacy-sensitive audio features for speaker diarization in multiparty conversations: ie., a set of audio features having low linguistic information for speaker diarization in a single and multiple distant microphone scenario ...
Speaker diarization is the task of identifying “who spoke when” in an audio stream containing multiple speakers. This is an unsupervised task as there is no a priori information about the speakers. Diagnostical studies on state-of-the-art diarization syste ...
The development of an Automatic Speech Recognition (ASR) system for the bilingual MediaParl corpus is challenging for several reasons: (1) reverberant recordings, (2) accented speech, and (3) no prior information about the language. In that context, we emp ...
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The development of an Automatic Speech Recognition (ASR) system for the bilingual MediaParl corpus is challenging for several reasons: (1) reverberant recordings, (2) accented speech, and (3) no prior information about the language. In that context, we emp ...
In this paper, we investigate employment of discriminatively trained acoustic features modeled by Subspace Gaussian Mixture Models (SGMMs) for Rich Transcription meeting recognition. More specifically, first, we focus on exploiting various types of complex ...
In this paper, we investigate employment of discriminatively trained acoustic features modeled by Subspace Gaussian Mixture Models (SGMMs) for Rich Transcription meeting recognition. More specifically, first, we focus on exploiting various types of complex ...
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