Characteristics of speaking style and implications for speech recognition.
Differences in speaking style are associated with more or less spectral variability, as well as different modulation characteristics. The greater variation in some styles (e.g., spontaneous speech and infant-directed speech) poses challenges for recognition but possibly also opportunities for learning more robust models, as evidenced by prior work and motivated by child language acquisition studies. In order to investigate this possibility, this work proposes a new method for characterizing speaking style (the modulation spectrum), examines spontaneous, read, adult-directed, and infant-directed styles in this space, and conducts pilot experiments in style detection and sampling for improved speech recognizer training. Speaking style classification is improved by using the modulation spectrum in combination with standard pitch and energy variation. Speech recognition experiments on a small vocabulary conversational speech recognition task show that sampling methods for training with a small amount of data benefit from the new features.
Shinozaki
Takahiro
T
Department of Electrical Engineering, University of Washington, Seattle, WA 98195-2500, USA.
Ostendorf
Mari
M
Atlas
Les
L
D001185:Artificial Intelligence; D001331:Automation; D019992:Databases as Topic; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D007398:Interpersonal Relations; D008297:Male; D010363:Pattern Recognition, Automated; D046709:Pattern Recognition, Physiological; D010865:Pilot Projects; D011932:Reading; D013018:Sound Spectrography; D013060:Speech; D013061:Speech Acoustics; D049250:Speech Recognition Software; D014825:Vocabulary