标题: | 适用于数位助听器之快速傅立叶转换系统的音高式噪音消除与回授消除技术设计 FFT Based Noise Reduction and Feedback Cancellation with Pitch Based Voice Activity Detector for Digital Hearing Aid System |
作者: | 林禹文 Lin, Yu-Wen 周世杰 Jou, Shyh-Jye 电子工程学系 电子研究所 |
关键字: | 助听器;杂讯消除;回授消除;语音区间侦测;音高;快速傅立叶;hearing aids;noise reduction;feedback cancellation;voice activity detection;pitch;fast Fourier transform |
公开日期: | 2014 |
摘要: | 随着制程以及讯号处理方面的进步之下,数位助听器已成为现在助听器主流。然而,由于目前助听器仍受限于电池容量太小,要实现复杂的演算法是很困难的。而到目前为止最有效的解决方式是透过有效率的低功耗演算法,架构以及电路设计去完成。在当前的助听器系统中有两个主要的问题。第一个问题是在嘈杂的环境下,我们对语音的理解度会下降。第二个问题是回授音的问题。为了解决这两个问题,我们提出了一个快速傅立叶转换的噪音消除以及回授消除的演算法。 我们所提出的音高式噪音消除演算法包含了音高式语音侦测器以及杂讯抑制器。音高式语音侦测器是利用语音里音高以及相对应的和谐音和子音起始的特性去侦测语音。为了更进一步改良我们的准确度,我们把两种方法结合来侦测音高以及相对应的和谐音。此外为了改善杂讯抑制器的效能,我们把原本的适用于QuasiANSI滤波器组的杂讯消除演算法修改成适用于快速傅立叶转换上,再加上两条曲线八个等级的分配增益机制,可有效改善PESQ。我们提出的音高式语音侦测器平均准确度可以分别在静态与动态背景杂讯环境里达到79.99%与80.31%。而提出的杂讯抑制器的语音区段讯杂比和语音讯杂比在静态背景杂讯环境中,平均改进6.09dB和8.86dB,在动态背景杂讯环境里平均改进6.49dB和9.28dB。另外,语音品质(PESQ)在静态与动态背景杂讯环境里平均改进0.31和0.46。 在回授消除部分也是根据快速傅立叶转换结果去设计,并设计出一个语音共振峰预估的方法。这个方法是利用音高的资讯去预估语音能量的分布,并用来辅助可适性回授消除演算法的系数更新,维持稳定的助听器增益及音质。我们所提出的可适性回授消除滤波器设计可达到跟预估错误方法的可适性回授消除滤波器有相似的可增加的稳定增益以及声音品质,而复杂度却可以比他们少四个数量级。 With the advanced technology and signal processing, digital hearing aids have been the main trend of hearing aids. However, it is difficult to implement a complicated algorithm due to the limitation of battery size and capacity. The effective way of solving this problem is to design an efficient low power algorithm, architecture and circuit. And there are two main problems in nowadays hearing aids system. The first problem is that the intelligibility may be degraded due to the background noise. The second problem is the echo from the speaker. In order to solve these two problems, we propose an FFT based noise reduction and feedback cancellation. The proposed pitch based noise reduction includes the pitch based voice activity detection and noise reduction algorithm. The pitch based VAD utilizes the pitch and its harmonics and onset characteristics of speech to detect speech activity. In order to improve the VAD accuracy, two kinds of methods are combined for pitch and harmonic detection. Besides, in order to improve the performance of NR, we modify the original pitch based NR algorithm applicable to Quasi-ANSI filter bank [1] to be more effective for noise reduction and it is applicable to FFT based decomposition. We add some mechanisms, like two curves eight levels gain assignment, to improve the PESQ. The accuracy rate of proposed pitch based VAD can achieve 79.99% and 80.31% in stationary and non-stationary noise environment respectively. And the average improvement of segmental signal-noise-ratio (SNRseg) and signal-noise-ratio (SNR) of the proposed noise reduction is 6.09dB and 8.86dB in stationary noise environment and 6.49dB and 9.28dB in non-stationary noise environment. Moreover, the average improvement of sound quality (PESQ) is 0.31 and 0.46 in stationary and non-stationary noise environments respectively. The design of feedback cancellation is based on FFT decomposition and a decorrelation filter coefficient update mechanism is proposed. The decorrelation filter coefficient update utilizes the pitch information to estimate speech formant to enhance the robustness and the sound quality of adaptive feedback cancellation (AFC). The proposed AFC design can achieve similar added stable gain (ASG) and PESQ but with four orders complexity reduction compared to PEM-AFC design. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT070150199 http://hdl.handle.net/11536/75820 |
显示于类别: | Thesis |