Whispering Speaker Identification

This paper describes a study of automatically identifying whispering speakers. People usually whisper in order to avoid being identified or overheard by lowering their voices. The study compares performances between normal and whispered speech mode in clean and noisy environment under matched and mismatched training conditions, and describes the impact of feature warping and throat microphone on noise reduction. Score combination strategies are used when only little whisper data is available to improve performance. In sum, we achieved 8% to 33% relative improvements in identification accuracy with only 5 to 10 seconds noisy whispered speech data per speaker.