title: Temporal resolution analysis in frequency domain linear prediction.
abstract: Frequency domain linear prediction (FDLP) is a technique for auto-regressive modeling of Hilbert envelopes. In this letter, the resolution properties of the FDLP model are investigated using synthetic signals with impulses immersed in noise. The effect of various factors are studied which affect the temporal resolution and this analysis suggests ways to improve the resolution of the FDLP envelopes in noisy speech. The high resolution FDLP envelopes are used to derive robust features for phoneme recognition in noisy and reverberant speech. In these experiments, the FDLP features derived from high resolution envelopes provide significant improvements.
authors.affiliation: IBM T. J. Watson Research Center, Yorktown Heights, New York 10562, USA. ganapath@us.ibm.com
authors.forename: Sriram
authors.initials: S
authors.lastname: Ganapathy
authors.forename: Hynek
authors.initials: H
authors.lastname: Hermansky
mesh_terms: D000161:Acoustic Stimulation; D000162:Acoustics; D005583:Fourier Analysis; D006801:Humans; D016014:Linear Models; D008390:Markov Chains; D016571:Neural Networks, Computer; D009622:Noise / Q000009:adverse effects; D010363:Pattern Recognition, Automated; D010470:Perceptual Masking; D013018:Sound Spectrography; D013061:Speech Acoustics; D013065:Speech Intelligibility; D013067:Speech Perception; D013997:Time Factors; D013998:Time Perception; D014732:Vibration