Loss recovery through spectral interpolation for robust speech recognition over packet voice communications

Packet voice communications generally suffer packet losses as a result of various network- or transmission-related impairments. Upon decoding, these lost packets result in missing speech segments that degrade automatic speech recognition (ASR) performance. We present a novel loss recovery scheme that reproduces the missing speech waveform by interpolating its spectrum from the speech spectra on both sides of a loss. An adaptive mechanism is used to determine the FFT width of the speech waveform before and after a loss to capture as much spectral detail as possible. A linearly weighted spectral interpolation ensues to obtain the spectra of missing speech. The missing speech waveform is then reconstructed through IFFT, followed by smoothing at packet boundaries. Tests on Bluetooth voice packets with a high loss rate of 38% show that our scheme improves ASR performance considerably (up to 20%) while being computationally efficient, as it is an FFT-based scheme.