首页> 外文会议>European Signal Processing Conference(EUSIPCO 2004) vol.2; 20040906-10; Vienna(AT) >LOSS RECOVERY THROUGH SPECTRAL INTERPOLATION FOR ROBUST SPEECH RECOGNITION OVER PACKET VOICE COMMUNICATIONS
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LOSS RECOVERY THROUGH SPECTRAL INTERPOLATION FOR ROBUST SPEECH RECOGNITION OVER PACKET VOICE COMMUNICATIONS

机译:通过频谱插值进行的丢失恢复,从而在分组语音通信中进行健壮的语音识别

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摘要

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.
机译:分组语音通信通常由于各种与网络或传输相关的损害而遭受分组丢失。在解码时,这些丢失的数据包会导致丢失语音片段,从而降低自动语音识别(ASR)性能。我们提出了一种新颖的损耗恢复方案,该方案通过从损耗两侧的语音频谱中插入其频谱来重现丢失的语音波形。自适应机制用于确定丢失前后的语音波形FFT宽度,以捕获尽可能多的频谱细节。随后进行线性加权频谱内插以获得丢失语音的频谱。然后通过IFFT重建丢失的语音波形,然后在数据包边界进行平滑处理。对具有38%的高丢失率的蓝牙语音数据包进行的测试表明,由于该方案是基于FFT的方案,因此可以显着提高ASR性能(高达20%),同时在计算效率上也很高。

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