2-D processing of speech

Abstract

Acoustic signals are analyzed by two-dimensional (2-D) processing of the one-dimensional (1-D) speech signal in the time-frequency plane. The short-space 2-D Fourier transform of a frequency-related representation (e.g., spectrogram) of the signal is obtained. The 2-D transformation maps harmonically-related signal components to a concentrated entity in the new 2-D plane (compressed frequency-related representation). The series of operations to produce the compressed frequency-related representation is referred to as the “grating compression transform” (GCT), consistent with sine-wave grating patterns in the frequency-related representation reduced to smeared impulses. The GCT provides for speech pitch estimation. The operations may, for example, determine pitch estimates of voiced speech or provide noise filtering or speaker separation in a multiple speaker acoustic signal.

Description

RELATED APPLICATION(S)[0001]This application claims the benefit of U.S. Provisional Application titled “2-D PROCESSING OF SPEECH” by Thomas F. Quatieri, Jr., Ser. No. 60 / 409,095, filed Sep. 6, 2002. The entire teaching of the above application is incorporated herein by reference.GOVERNMENT SUPPORT[0002]The invention was supported, in whole or in part, by the United States Government's Technical Support Working Group under Air Force Contract No. F19628-00-C-0002. The Government has certain rights in the invention.BACKGROUND OF THE INVENTION[0003]Conventional processing of acoustic signals (e.g., speech) analyzes a one dimensional frequency signal in a frequency-time domain. Sinewave-base techniques (e.g., the sine-wave-based pitch estimator described in R. J. McAulay and T. F. Quatieri, “Pitch estimation and voicing detection based on a sinusoidal model,” Proc. lnt. Conf. on Acoustics, Speech, and Signal Processing, Albuquerque, N.Mex., pp. 249–252, 1990) have been used to estimate t...

AI Technical Summary

Benefits of technology

[0005]A method of processing an acoustic signal is provided that prepares a frequency-related representation of the acoustic signal over time (e.g., spectrogram, wavelet transform or auditory transform) and computes a two dimensional transform, such as a 2-D Fourier transform, of the frequency-related representation to provide a compressed frequency-related representation. The compressed frequency-related representation is then processed. The acoustic signal can be a speech signal and the processing may determine a pitch of the speech signal. The pitch of the speech signal can be determined from computing the inverse of a distance between a peak of impulses and an origin. Windowing (e.g., Hamming windows) of the spectrogram can be used to further improve the calculation of the pitch estimate; likewise a multiband analysis is performed for further improvement.

[0006]Processing of the compressed frequency-related representation may filter noise from the acoustic signal. Processing of the compressed frequency-related representation may distinguish plural sources (e.g., separate speakers) within the acoustic signal by filtering the compressed frequency-related representation and performing an inverse transform.

[0007]An embodiment of the present invention produces pitch estimation on par with conventional sinewave-based pitch estimation techniques and performs better than conventional sinewave-based pitch estimation techniques in noisy environments. This embodiment of the present invention for pitch estimation also performs well with high pitch (e.g., women's) speech.

Problems solved by technology

Conventional pitch estimation techniques often suffer when presented with noisy environments or high pitch (e.g., women's) speech.

Processing of the compressed frequency-related representation may filter noise from the acoustic signal.